metaseqR report

Summary

Analysis summary

Summary: The gene counts table was normalized for inherent systematic or experimental biases (e.g. sequencing depth, gene length, GC content bias etc.) using the Bioconductor package DESeq after removing gene s that had zero counts over all the RNA-Seq samples (22031 genes). The output of the normalization algorithm was a table with normalized counts, which can be used for differential expression analysis with statistical algorithms developed specifically for count data. Prior to the statistical testing procedure, the gene read counts were filtered for possible artifacts that could affect the subsequent statistical testing procedures. Genes/transcripts presenting any of the following were excluded from further analysis: i) genes with length less than 500 (3747 genes), ii) genes whose average reads per 100 bp was less than the 25^th quantile of the total normalized distribution of average reads per 100bp (0 genes with cutoff value 0.02961 average reads per 100 bp), iii) genes with read counts below the median read counts of the total normalized count distribution (11710 genes with cutoff value 12 normalized read counts), iv) genes whose biotype matched the following: rRNA, IG_V_pseudogene, TR_V_pseudogene (60 genes). The total number of genes excluded due to the application of gene filters was 4816. The total (unified) number of genes excluded due to the application of all filters was 34846. The resulting gene counts table was subjected to differential expression analysis for the contrasts Cond1 versus Cond2 using the Bioconductor package DESeq. The final numbers of differentially expressed gene s were (per contrast): for the contrast Cond1 versus Cond2, 1608 (209) statistically significant genes were found with a p-value (FDR or adjusted p-value) threshold of 0.05 and of these, 255 (62) were up-regulated, 558 (138) were down-regulated and 795 (9) were not differentially expressed according to an absolute fold change cutoff value of 1 in log₂ scale. Literature references for all the algorithms used can be found at the end of this report.

Input options

Read counts file: imported custom data frame
Conditions: Cond1, Cond2
Samples included: ED3R9, ED3R10, ED3R11, ED3R12, ED3R13, ED3R14, ED3R15, ED3R16
Samples excluded: none
Requested contrasts: Cond1_vs_Cond2
Library sizes: not available
Annotation: embedded
Organism:
Annotation source: Ensembl genomes
Count type: utr
3' UTR flanking :: 500
Exon filters: none applied
Gene filters: length, avg.reads, expression, biotype

length
- length: 500

avg.reads
- average.per.bp: 100
- quantile: 0.25

expression
- median: TRUE
- mean: FALSE
- quantile: NA
- known: NA
- custom: NA

biotype
- pseudogene: FALSE
- snRNA: FALSE
- protein_coding: FALSE
- antisense: FALSE
- miRNA: FALSE
- snoRNA: FALSE
- lincRNA: FALSE
- processed_transcript: FALSE
- misc_RNA: FALSE
- rRNA: TRUE
- sense_intronic: FALSE
- sense_overlapping: FALSE
- polymorphic_pseudogene: FALSE
- IG_C_gene: FALSE
- IG_J_gene: FALSE
- IG_D_gene: FALSE
- IG_LV_gene: FALSE
- IG_V_gene: FALSE
- IG_V_pseudogene: TRUE
- TR_V_gene: FALSE
- TR_V_pseudogene: TRUE
- three_prime_overlapping_ncrna: FALSE

Filter application: after normalization
Normalization algorithm: DESeq
Normalization arguments: locfunc

[[list(new("standardGeneric", .Data = function (x, na.rm = FALSE, ...) standardGeneric("median"), generic = "median", package = "stats", group = list(), valueClass = character(0), signature = c("x", "na.rm"), default = new("derivedDefaultMethod", .Data = function (x, na.rm = FALSE, ...) UseMethod("median"), target = new("signature", .Data = "ANY", names = "x", package = "methods"), defined = new("signature", .Data = "ANY", names = "x", package = "methods"), generic = "median"), skeleton = (new("derivedDefaultMethod", .Data = function (x, na.rm = FALSE, ...) UseMethod("median"), target = new("signature", .Data = "ANY", names = "x", package = "methods"), defined = new("signature", .Data = "ANY", names = "x", package = "methods"), generic = "median"))(x, na.rm, ...)))locfunc

Statistical algorithm(s): DESeq
Statistical arguments for DESeq: method, sharingMode, fitType

method: blind
sharingMode: fit-only
fitType: local

Meta-analysis method: no meta-analysis, reported p-values from the first supplied statistical algorithm
Multiple testing correction: Benjamini-Hochberg FDR
p-value threshold: 0.05
Logarithmic tranformation offset: 1
Analysis preset: not available
Quality control plots: multidimensional scaling, biotype detection, biotype counts, sample and biotype saturation, filtered biotypes, correlation heatmap and correlogram, pairwise scatterplots between samples, boxplots, GC-content bias, transcript length bias, mean-difference plot, mean-variance plot, DEG biotype detection, volcano plot, DEG heatmap
Figure format: png, pdf
Output directory: /data/images/proton3/run464/EDlab/metaseqr_run464
Output data: Annotation, p-value, Adjusted p-value (FDR), Fold change, Statistics, Read counts
Output scale(s): log2 scale, Reads per Gene Model
Output values: Normalized values
Output statistics: Mean
Total run time: 06 minutes 42 seconds

Filtered genes

Number of filtered gene s: 34846 which is the union of

Filtered because of zero reads: 22031
Filtered because of exon filters: 0
Filtered because of gene filters: 12815 which is the union of
- length: 3747 genes with filter cutoff value 500
- avg.reads: 1008 genes with filter cutoff value 0.02961427
- expression: 11710 genes further decomposed to (filter name, filtered genes, filter cutoff):
- - median: 11710 genes with filter cutoff value 12
- biotype: 60 genes with filter cutoff value rRNA, IG_V_pseudogene, TR_V_pseudogene

Differentially expressed genes

Number of differentially expressed genes per contrast:

Cond1_vs_Cond2: 1608 (209) statistically significant genes of which 255 (62) up regulated, 558 (138) down regulated and 795 (9) not differentially expressed according to a p-value (FDR or adjusted p-value) threshold of 0.05 and an absolute fold change cutoff value of 1 in log₂ scale.

Run log

INFO [2021-02-22 18:30:10] 2021-02-22 18:30:10: Data processing started...
INFO [2021-02-22 18:30:10] Read counts file: imported custom data frame
INFO [2021-02-22 18:30:10] Conditions: Cond1, Cond2
INFO [2021-02-22 18:30:10] Samples to include: ED3R9, ED3R10, ED3R11, ED3R12, ED3R13, ED3R14, ED3R15, ED3R16
INFO [2021-02-22 18:30:10] Samples to exclude: none
INFO [2021-02-22 18:30:10] Requested contrasts: Cond1_vs_Cond2
INFO [2021-02-22 18:30:10] Annotation: embedded
INFO [2021-02-22 18:30:10] Organism: custom
INFO [2021-02-22 18:30:10] Reference source: ensembl
INFO [2021-02-22 18:30:10] Count type: utr
INFO [2021-02-22 18:30:10] 3' UTR flanking: 500
INFO [2021-02-22 18:30:10] Transcriptional level: gene
INFO [2021-02-22 18:30:10] Exon filters: none applied
INFO [2021-02-22 18:30:10] Gene filters: length, avg.reads, expression, biotype
INFO [2021-02-22 18:30:10] length:
INFO [2021-02-22 18:30:10] length: 500
INFO [2021-02-22 18:30:10] avg.reads:
INFO [2021-02-22 18:30:10] average.per.bp: 100
INFO [2021-02-22 18:30:10] quantile: 0.25
INFO [2021-02-22 18:30:10] expression:
INFO [2021-02-22 18:30:10] median: TRUE
INFO [2021-02-22 18:30:10] mean: FALSE
INFO [2021-02-22 18:30:10] quantile: NA
INFO [2021-02-22 18:30:10] known: NA
INFO [2021-02-22 18:30:10] custom: NA
INFO [2021-02-22 18:30:10] biotype:
INFO [2021-02-22 18:30:10] pseudogene: FALSE
INFO [2021-02-22 18:30:10] snRNA: FALSE
INFO [2021-02-22 18:30:10] protein_coding: FALSE
INFO [2021-02-22 18:30:10] antisense: FALSE
INFO [2021-02-22 18:30:10] miRNA: FALSE
INFO [2021-02-22 18:30:10] snoRNA: FALSE
INFO [2021-02-22 18:30:10] lincRNA: FALSE
INFO [2021-02-22 18:30:10] processed_transcript: FALSE
INFO [2021-02-22 18:30:10] misc_RNA: FALSE
INFO [2021-02-22 18:30:10] rRNA: TRUE
INFO [2021-02-22 18:30:10] sense_intronic: FALSE
INFO [2021-02-22 18:30:10] sense_overlapping: FALSE
INFO [2021-02-22 18:30:10] polymorphic_pseudogene: FALSE
INFO [2021-02-22 18:30:10] IG_C_gene: FALSE
INFO [2021-02-22 18:30:10] IG_J_gene: FALSE
INFO [2021-02-22 18:30:10] IG_D_gene: FALSE
INFO [2021-02-22 18:30:10] IG_LV_gene: FALSE
INFO [2021-02-22 18:30:10] IG_V_gene: FALSE
INFO [2021-02-22 18:30:10] IG_V_pseudogene: TRUE
INFO [2021-02-22 18:30:10] TR_V_gene: FALSE
INFO [2021-02-22 18:30:10] TR_V_pseudogene: TRUE
INFO [2021-02-22 18:30:10] three_prime_overlapping_ncrna: FALSE
INFO [2021-02-22 18:30:10] Filter application: postnorm
INFO [2021-02-22 18:30:10] Normalization algorithm: deseq
INFO [2021-02-22 18:30:10] Normalization arguments:
INFO [2021-02-22 18:30:10] locfunc:
INFO [2021-02-22 18:30:10] [[list(new("standardGeneric", .Data = function (x, na.rm = FALSE, ...) standardGeneric("median"), generic = "median", package = "stats", group = list(), valueClass = character(0), signature = c("x", "na.rm"), default = new("derivedDefaultMethod", .Data = function (x, na.rm = FALSE, ...) UseMethod("median"), target = new("signature", .Data = "ANY", names = "x", package = "methods"), defined = new("signature", .Data = "ANY", names = "x", package = "methods"), generic = "median"), skeleton = (new("derivedDefaultMethod", .Data = function (x, na.rm = FALSE, ...) UseMethod("median"), target = new("signature", .Data = "ANY", names = "x", package = "methods"), defined = new("signature", .Data = "ANY", names = "x", package = "methods"), generic = "median"))(x, na.rm, ...)))locfunc
INFO [2021-02-22 18:30:10] Statistical algorithm: deseq
INFO [2021-02-22 18:30:10] Statistical arguments:
INFO [2021-02-22 18:30:10] deseq: blind, fit-only, local
INFO [2021-02-22 18:30:10] Meta-analysis method: none
INFO [2021-02-22 18:30:10] Multiple testing correction: BH
INFO [2021-02-22 18:30:10] p-value threshold: 0.05
INFO [2021-02-22 18:30:10] Logarithmic transformation offset: 1
INFO [2021-02-22 18:30:10] Quality control plots: mds, biodetection, countsbio, saturation, readnoise, filtered, correl, pairwise, boxplot, gcbias, lengthbias, meandiff, meanvar, biodist, volcano, deheatmap
INFO [2021-02-22 18:30:10] Figure format: png, pdf
INFO [2021-02-22 18:30:10] Output directory: /data/images/proton3/run464/EDlab/metaseqr_run464
INFO [2021-02-22 18:30:10] Output data: annotation, p.value, adj.p.value, fold.change, stats, counts, flags
INFO [2021-02-22 18:30:10] Output scale(s): log2, rpgm
INFO [2021-02-22 18:30:10] Output values: normalized
INFO [2021-02-22 18:30:10] Output statistics: mean
INFO [2021-02-22 18:30:10] Reading custom external gene annotation for from /data/results/tools/rnaseq/metaseqr/mm10/gene_data_mm10.txt.gz...
INFO [2021-02-22 18:30:11] Checking chromosomes in transcript counts and gene annotation...
INFO [2021-02-22 18:30:11] Processing transcripts...
INFO [2021-02-22 18:30:11] Separating transcripts (UTR regions) per for ED3R9...
INFO [2021-02-22 18:30:30] Separating transcripts (UTR regions) per for ED3R10...
INFO [2021-02-22 18:30:46] Separating transcripts (UTR regions) per for ED3R11...
INFO [2021-02-22 18:31:02] Separating transcripts (UTR regions) per for ED3R12...
INFO [2021-02-22 18:31:19] Separating transcripts (UTR regions) per for ED3R13...
INFO [2021-02-22 18:31:38] Separating transcripts (UTR regions) per for ED3R14...
INFO [2021-02-22 18:31:55] Separating transcripts (UTR regions) per for ED3R15...
INFO [2021-02-22 18:32:14] Separating transcripts (UTR regions) per for ED3R16...
INFO [2021-02-22 18:32:36] Saving gene model to /data/images/proton3/run464/EDlab/metaseqr_run464/data/gene_model.RData
INFO [2021-02-22 18:32:41] Summarizing count data...
INFO [2021-02-22 18:32:49] Removing genes with zero counts in all samples...
INFO [2021-02-22 18:32:49] Normalizing with: deseq
INFO [2021-02-22 18:32:50] Applying gene filter length...
INFO [2021-02-22 18:32:50] Threshold below which ignored: 500
INFO [2021-02-22 18:32:50] Applying gene filter avg.reads...
INFO [2021-02-22 18:32:50] Threshold below which ignored: 0.0296142740801066
INFO [2021-02-22 18:32:50] Applying gene filter expression...
INFO [2021-02-22 18:32:50] Threshold below which ignored: 12
INFO [2021-02-22 18:32:50] Applying gene filter biotype...
INFO [2021-02-22 18:32:50] Biotypes ignored: rRNA, IG_V_pseudogene, TR_V_pseudogene
INFO [2021-02-22 18:32:51] 34846 genes filtered out
INFO [2021-02-22 18:32:51] 14702 genes remain after filtering
INFO [2021-02-22 18:32:51] Running statistical tests with: deseq
INFO [2021-02-22 18:32:51] Contrast: Cond1_vs_Cond2
INFO [2021-02-22 18:33:07] Contrast Cond1_vs_Cond2: found 1608 genes
INFO [2021-02-22 18:33:07] Building output files...
INFO [2021-02-22 18:33:09] Contrast: Cond1_vs_Cond2
INFO [2021-02-22 18:33:09] Adding non-filtered data...
INFO [2021-02-22 18:33:09] binding annotation...
INFO [2021-02-22 18:33:09] binding p-values...
INFO [2021-02-22 18:33:10] binding FDRs...
INFO [2021-02-22 18:33:10] binding log2 normalized fold changes...
INFO [2021-02-22 18:33:10] binding normalized mean counts...
INFO [2021-02-22 18:33:10] binding normalized mean counts...
INFO [2021-02-22 18:33:11] binding all normalized counts for Cond1...
INFO [2021-02-22 18:33:11] binding all normalized counts for Cond2...
INFO [2021-02-22 18:33:12] binding filtering flags...
INFO [2021-02-22 18:33:12] Writing output...
INFO [2021-02-22 18:33:12] Adding filtered data...
INFO [2021-02-22 18:33:12] binding annotation...
INFO [2021-02-22 18:33:12] binding p-values...
INFO [2021-02-22 18:33:12] binding FDRs...
INFO [2021-02-22 18:33:13] binding log2 normalized fold changes...
INFO [2021-02-22 18:33:13] binding normalized mean counts...
INFO [2021-02-22 18:33:14] binding normalized mean counts...
INFO [2021-02-22 18:33:15] binding all normalized counts for Cond1...
INFO [2021-02-22 18:33:15] binding all normalized counts for Cond2...
INFO [2021-02-22 18:33:15] binding filtering flags...
INFO [2021-02-22 18:33:15] Writing output...
INFO [2021-02-22 18:33:18] Creating quality control graphs...
INFO [2021-02-22 18:33:18] Plotting in png format...
INFO [2021-02-22 18:33:18] Plotting mds...
INFO [2021-02-22 18:33:18] Plotting biodetection...
INFO [2021-02-22 18:33:19] Plotting countsbio...
INFO [2021-02-22 18:33:20] Plotting saturation...
INFO [2021-02-22 18:33:28] Plotting readnoise...
INFO [2021-02-22 18:33:29] Plotting correl...
INFO [2021-02-22 18:33:29] Plotting pairwise...
INFO [2021-02-22 18:33:48] Plotting boxplot...
INFO [2021-02-22 18:33:48] Plotting gcbias...
INFO [2021-02-22 18:33:49] Plotting lengthbias...
INFO [2021-02-22 18:33:49] Plotting meandiff...
INFO [2021-02-22 18:33:51] Plotting meanvar...
INFO [2021-02-22 18:34:13] Plotting boxplot...
INFO [2021-02-22 18:34:13] Plotting gcbias...
INFO [2021-02-22 18:34:14] Plotting lengthbias...
INFO [2021-02-22 18:34:15] Plotting meandiff...
INFO [2021-02-22 18:34:16] Plotting meanvar...
INFO [2021-02-22 18:34:39] Plotting biodist...
INFO [2021-02-22 18:34:39] Contrast: Cond1_vs_Cond2
INFO [2021-02-22 18:34:40] Plotting volcano...
INFO [2021-02-22 18:34:40] Contrast: Cond1_vs_Cond2
INFO [2021-02-22 18:34:40] Plotting deheatmap...
INFO [2021-02-22 18:34:40] Contrast: Cond1_vs_Cond2
INFO [2021-02-22 18:35:11] Plotting filtered...
INFO [2021-02-22 18:35:11] Plotting in pdf format...
INFO [2021-02-22 18:35:11] Plotting mds...
INFO [2021-02-22 18:35:11] Plotting biodetection...
INFO [2021-02-22 18:35:12] Plotting countsbio...
INFO [2021-02-22 18:35:13] Plotting saturation...
INFO [2021-02-22 18:35:18] Plotting readnoise...
INFO [2021-02-22 18:35:19] Plotting correl...
INFO [2021-02-22 18:35:19] Plotting pairwise...
INFO [2021-02-22 18:35:29] Plotting boxplot...
INFO [2021-02-22 18:35:29] Plotting gcbias...
INFO [2021-02-22 18:35:30] Plotting lengthbias...
INFO [2021-02-22 18:35:31] Plotting meandiff...
INFO [2021-02-22 18:35:33] Plotting meanvar...
INFO [2021-02-22 18:35:56] Plotting boxplot...
INFO [2021-02-22 18:35:56] Plotting gcbias...
INFO [2021-02-22 18:35:57] Plotting lengthbias...
INFO [2021-02-22 18:35:57] Plotting meandiff...
INFO [2021-02-22 18:36:00] Plotting meanvar...
INFO [2021-02-22 18:36:23] Plotting biodist...
INFO [2021-02-22 18:36:23] Contrast: Cond1_vs_Cond2
INFO [2021-02-22 18:36:23] Plotting volcano...
INFO [2021-02-22 18:36:23] Contrast: Cond1_vs_Cond2
INFO [2021-02-22 18:36:24] Plotting deheatmap...
INFO [2021-02-22 18:36:24] Contrast: Cond1_vs_Cond2
INFO [2021-02-22 18:36:51] Plotting filtered...
INFO [2021-02-22 18:36:51] Creating HTML report...
INFO [2021-02-22 18:36:51] Compressing figures...

Figures

Multidimensional scaling

The Multi-Dimensional Scaling (MDS) plots comprise a means of visualizing the level of similarity of individual cases of a dataset. It is similar to Principal Component Analysis (PCA), but instead of using the covariance matrix to find similarities among cases, MDS uses absolute distance metrics such as the classical Euclidean distance. Because of the relative linear relations among sequencing samples, it provides a more realistic clustering among samples. MDS serves quality control and it can be interpreted as follows: when the distance among samples of the same biological condition in the MDS space is small, this is an indication of high correlation and reproducibility among them. When this distance is larger or heterogeneous (e.g. the 3rd sample of a triplicate set is further from the other 2), this constitutes an indication of low correlation and reproducibility among samples. It can help exclude poor samples from further analysis.

Biotype detection

The biotype detection bar diagrams are a set of quality control charts that show the percentage of each biotype in the genome (i.e. in the whole set of features provided, for example, protein coding genes, non coding RNAs or pseudogenes) in grey bars, which proportion has been detected in a sample before normalization and after a basic filtering by removing features with zero counts in red lined bars, and the percentage of each biotype within the sample in solid red bars. The difference between grey bars and solid red bars is that the grey bars show the percentage of a feature in the genome while the solid red bars show the percentage in the sample. Thus, the solid red bars may be sometimes higher than the grey bars because certain features (e.g. protein coding genes) may be detected within a sample with a higher proportion relatively to their presence in the genome, as compared with other features. For example, while the percentage of protein coding genes in the whole genome is already higher than other biotypes, this percentage is expected to be even higher in an RNA-Seq experiment where one expects protein-coding genes to exhibit greater abundance. The vertical green line separates the most abundant biotypes (on the left-hand side, corresponding to the left axis scale) from the rest (on the right-hand side, corresponding to the right axis scale). Otherwise, the lower abundance biotypes would be indistinguishable. Unexpected outcomes in this quality control chart (e.g. very low detection of protein coding genes) would signify possible low quality of a sample.

Biotype detection counts

The biotype detection counts boxplots are a set of quality control charts that depict both the biological classification for the detected features and the actual distribution of the read counts for each biological type. The boxplot comprises a means of summarizing the read counts distribution of a sample in the form of a bar with extending lines, as commonly used way of graphically presenting groups of numerical data. A boxplot also indicates which observations, if any, might be considered outliers and is able to visually show different types of populations, without making any assumptions of the underlying statistical distribution. The spacing between the different parts of the box help indicate variance, skewness and identify outliers. The thick bar inside the colored box is the median of the observations while the box extends over the Interquartile Range of the observations. The whiskers extend up (down) to +/-1.5xIQR. Unexpected outcomes (e.g. protein coding read count distribution similar to pseudogene read count distribution) indicates poor sample quality.

Read and biotype saturation

The read and biotype saturation plots are a set of quality control charts that depict the read count saturation levels at several sequencing depths. Thus, they comprise a means of assessing whether the sequencing depth of an RNA-Seq experiment is sufficient in order to detect the biological features under investigation. These quality control charts are separated in two subgroups: the first subgroup (read saturation per biotype for all samples) is a set of plots, one for each biological feature (e.g. protein coding, pseudogene, lincRNA, etc.), that depict the number of detected features in different sequencing depths and for all samples in the same plot. The second subgroup (read saturation per sample for all biotypes) is a set of plots similar to the above, but with, there is one pair of plots with two panels for each sample, presenting all biological features. The left panel depicts the saturation levels for the less abundatnt features, while the right panel, the saturation for the more abundant features, as placing them all together would make the less abundant features indistinguishable. All the saturation plots should be interpreted as follows: if the read counts for a biotype tend to be saturated, the respective curve should tend to reach a plateau at higher depths. Otherwise, more sequencing is needed for the specific biotype.

Read saturation per biotype for all samples

Read saturation per sample for all biotypes

RNA-Seq reads noise

The read noise plots depict the percentage of biological features detected when subsampling the total number of reads. Very steep curves in read noise plots indicate that although the sequencing depth reaches its maximum, a relatively small percentage of total features is detected, indicating that the level of background noise is relatively high. Less steep RNA composition curves, indicate less noise. When a sample's curve deviate from the rest, it could indicate lower or higher quality, depending on the curves of the rest of the samples.

Correlation plots

The sample correlation plots depict the accordance among the RNA-Seq samples, as this is manifested through the read counts table used with the metaseqr pipeline, with two representations that both use the correlation matrix (a matrix which depicts all the pairwise correlations between each pair of samples) of the read counts matrix. The first is a correlation clustered heatmap which depicts the correlations among samples as color-scaled image and the hierarchical clustering tree depicts the grouping of the samples according to their correlation. Samples from the same group that are not clustered together provides an indication that there might be a quality problem with the dataset. The second is a 'correlogram' plot, where again the samples are hierarchically clustered and grouped but this time correlations are presented as ellipses inside each cell. Each cell represents a pairwise comparison and each correlation coefficient is represented by an ellipse whose 'diameter', direction and color depict the accordance for that pair of samples. Highly correlated samples are depicted as ellipses with narrow diameter, while poorly correlated samples are depicted as ellipses with wide diameters. Also, highly correlated samples are depicted as ellipses with a left-to-right upwards direction while poorly correlated samples are depicted as ellipses with a right-to-left upwards direction.

Correlation heatmap

Data correlogram

Pairwise scatterplots

The pairwise comparison plots are split in three parts: the upper diagonal consists of simple scatterplots for all pairwise sample comparisons, together with their Pearson correlation coefficient. It is a simple measure of between sample correlation using all the available data points instead of only the correlation matrix. The lower diagonal consists of mean-difference plots for all pairwise sample comparisons. A mean-difference plot (or a Bland-Altman plots) is a method of data plotting used in analyzing the agreement between two different assays/variables. In this graphical method the differences (or alternatively the ratios) between the two variables are plotted against the averages of the two. Such a plot is useful, for example, for analyzing data with strong correlation between x and y axes, when the (x,y) dots on the plot are close to the diagonal x=y. In this case, the value of the transformed variable X is about the same as x and y and the variable Y shows the difference between x and y. In both represantations, irregular shapes of the red smoother lines are an indication of poor correlation between samples or of other systematic bias sources, which is usually corrected through data normalization.

Boxplots

The boxplot comprises a means of summarizing the read counts distribution of a sample in the form of a bar with extending lines, as a commonly used way of graphically presenting groups of numerical data. A boxplot also indicates which observations, if any, might be considered outliers and is able to visually show different types of populations, without making any assumptions about the underlying statistical distribution. The spacings between the different parts of the box help indicate variance, skewness and identify outliers. The thick bar inside the colored box is the median of the observations while the box extends over the Interquartile Range of the observations. The whiskers extend up (down) to +/-1.5xIQR. Boxplots at similar levels indicate good quality of the normalization. If boxplots remain at different levels after normalization, maybe another normalization algorithm may have to be examined. The un-normalized boxplots show the need for data normalization in order for the data from different samples to follow the same underlying distribution and statistical testing becoming possible.

Boxplot of un-normalized data

Boxplot of normalized data

GC content bias

The GC-content bias plot is a quality control chart that shows the possible dependence of the read counts (in log2 scale) under a gene to the GC content percentage of that gene. In order for the statistical tests to be able to detect statistical significance which occurs due to real biological effects and not by other systematic biases present in the data (e.g. a possible GC-content bias), the latter should be accounted for by the applied normalization algorithm. Although the tests are performed for each gene across biological conditions one could assume that the GC content does not represent a bias, as it is the same for the tested gene across samples and conditions. However, Risso et al. (2011) showed that the GC-content could have an impact in the statistical testing procedure. The GC-content bias plot depicts the dependence of the read counts to the GC content before and after normalization. The smoothing lines for each sample, should be as 'straight' as possible after normalization. In addition, if the smoothing lines differ significantly between biological conditions, this would constitute a possible quality warning.

GC content bias un-normalized

GC content bias normalized

Gene/transcript length bias

The gene/transcript length bias plot is a quality control chart that shows the possible dependence of the read counts (in log2 scale) under a gene to the length that gene (whole gene or sum of exons depending on the analysis). In order for the statistical tests to be able to detect statistical significance which occurs due to real biological effects and not by other systematic biases present in the data (e.g. a possible length bias), the latter should be accounted for by the applied normalization algorithm. Although the tests are performed for each gene across bioogical conditions, one could assume that the gene length does not represent a bias as it's the same for the tested gene across samples and conditions. However, it has been shown in several studies that the gene length could have an impact on the statistical testing procedure. The length bias plot depicts the dependence of the read counts to the gene/transcript length before and after normalization. The smoothing lines for each sample, should be as 'straight' as possible after normalization. In addition, if the smoothing lines differ significantly among biological conditions, this would constitute a possible quality warning.

Gene/transcript length bias un-normalized

Gene/transcript length bias normalized

Mean-difference

A mean-difference plot (or a Bland-Altman plot) is a method of data plotting used in analyzing the agreement between two different assays/variables. In this graphical method the differences (or alternatively the ratios) between the two variables are plotted against the averages of the two. Such a plot is useful, for example, for analyzing data with strong correlation between x and y axes, when the (x,y) dots on the plot are close to the diagonal x=y. In this case, the value of the transformed variable X is about the same as x and y and the variable Y shows the difference between x and y. When the data cloud in a mean difference plot is centered around the horizontal zero line, this is an indication of good data quality and good normalization results. On the other hand, when the data cloud deviates from the center line or has a 'banana' shape, this constitutes an indication of systematic biases present in the data and that either the chosen normalization algorithm has not worked well, or that data are not normalized. The smoothing curve that traverses the data (red curve) summarizes the above trends.

Mean-difference plots for the replicates of Cond1

Mean-difference plots for the replicates of Cond2

Mean-variance

The mean-variance plot comprises a graphical means of displaying a possible relationship between the means of gene expression (counts) values and their variances across replicates of the same biological condition. Thus data can be inspected for possible overdispersion (greater variability in a dataset than would be expected based on a given simple statistical model). In such plots for RNA-Seq data, overdispersion is usually manifested as increasing variance with increasing gene expression (counts) and it is summarized through a smoothing curve (red curve). The following is taken from the EDASeq package vignette: '...although the Poisson distribution is a natural and simple way to model count data, it has the limitation of assuming equality of the mean and variance. For this reason, the negative binomial distribution has been proposed as an alternative when the data show over-dispersion...' If overdispersion is not present, the data cloud is expected to be evenly scattered around the smoothing curve.

Mean-variance plots for the replicates of Cond1

Mean-variance plots for the replicates of Cond2

Chromosome and biotype distribution of filtered gene s

The chromosome and biotype distribution of filtered genes is a quality control chart with two rows and four panels: on the left panel of the first row, the bar chart depicts the numbers of filtered genes per chromosome (actual numbers shown above the bars). On the right panel of the first row, the bar chart depicts the numbers of filtered genes per biotype (actual numbers shown above the bars). On the left panel of the second row, the bar chart depicts the fraction of the filtered genes to the total genes per chromosome (actual percentages shown above the bars). On the right panel of the second row, the bar chart depicts the fraction of the filtered genes to the total genes per biotype (actual percentages shown above the bars). This plot should indicate possible quality problems when for example the filtered genes for a specific chromosome (or the fraction) is extremely higher than the rest. Generally, the fractions per chromosome should be uniform and the fractions per biotype should be proportional to the biotype fraction relative to the genome.

Volcano plots

A volcano plot is a scatterplot that is often used when analyzing high-throughput -omics data (e.g. microarray data, RNA-Seq data) to give an overview of interesting genes. The log2 fold change is plotted on the x-axis and the negative log10 p-value is plotted on the y-axis. A volcano plot combines the results of a statistical test (aka, p-values) with the magnitude of the change enabling quick visual identification of those genes that display large-magnitude changes that are also statistically significant. The horizontal dashed line sets the threshold for statistical significance, while the vertical dashed lines set the thresholds for biological significance. It should be noted that the volcano plots become harder to interpret when using more than one statistical algorithm and performing meta-analysis. This happens because the genes that have stronger evidence of being differentially expressed obtain lower p-values while the rest either remain at similar levels or obtain higher p-values. The result is a 'warped' volcano plot, with two main data clouds: one in the upper part of the plot, and one in the lower part of the plot. You can always zoom in when using interacting mode (the default).

Volcano plot for the contrast Cond1_vs_Cond2

DEG heatmaps

The Differentially Expressed Genes (DEGs) heatmaps depict how well samples from different conditions cluster together according to their expression values after normalization and statistical testing, for each requested statistical contrast. If samples from the same biological condition do not cluster together, this would constitute a warning sign regarding the quality of the samples. In addition, DEG heatmaps provide an initial view of possible clusters of co-expressed genes.

DEG heatmap for the contrast Cond1_vs_Cond2

Chromosome and biotype distributions of DEGs

The chromosome and biotype distributions bar diagram for Differentially Expressed Genes (DEGs) is split in two panels: i) on the left panel DEGs are distributed per chromosome and the percentage of each chromosome in the genome is presented in grey bars, the percentage of DEGs in each chromosome is presented in red lined bars and the percentage of certain chromosomes in the distribution of DEGs is presented in solid red bars. ii) on the right panel, DEGs are distributed per biotype and the percentage of each biotype in the genome (i.e. in the whole set of features provided, for example, protein coding genes, non coding RNAs or pseudogenes) is presented in grey bars, the percentage of DEGs in each biotype is presented in blue lined bars and the percentage of each biotype in DEGs is presented in solid blue lines. The vertical green line separates the most abundant biotypes (on the left-hand side, corresponding to the left axis scale), from the rest (on the right-hand side, corresponding to the right axis scale). Otherwise, the lower abundance, biotypes would be indistinguishable.

Biotype distribution in DEG for the contrast Cond1_vs_Cond2

Get all the figures in png, pdf format.

Results

DEG table for the contrast Cond1_vs_Cond2

The following table presents the top 10% statistically significant genes (use the download links below the table to retrieve the whole list) for the contrast Cond1_vs_Cond2. The fields of the table correspond to the requested features to be exported. The table can be searched using the search field on the top right.

chromosome	start	end	gene_id	gc_content	strand	gene_name	biotype	p-value_deseq	FDR_deseq	log2_normalized_fold_change_Cond1_vs_Cond2	log2_normalized_mean_counts_Cond1	rpgm_normalized_mean_counts_Cond1	log2_normalized_mean_counts_Cond2	rpgm_normalized_mean_counts_Cond2	log2_normalized_counts_ED3R9	log2_normalized_counts_ED3R10	log2_normalized_counts_ED3R11	log2_normalized_counts_ED3R12	rpgm_normalized_counts_ED3R9	rpgm_normalized_counts_ED3R10	rpgm_normalized_counts_ED3R11	rpgm_normalized_counts_ED3R12	log2_normalized_counts_ED3R13	log2_normalized_counts_ED3R14	log2_normalized_counts_ED3R15	log2_normalized_counts_ED3R16	rpgm_normalized_counts_ED3R13	rpgm_normalized_counts_ED3R14	rpgm_normalized_counts_ED3R15	rpgm_normalized_counts_ED3R16
chr5	25369020	25373039	ENSMUSG00000106457	35.45	+	Gm42585	TEC	1.76e-19	2.59e-15	6.243174	0.00e+00	0.00e+00	3.30e+00	5.96e-02	0.00e+00	0.00e+00	0.00e+00	0.00e+00	0.00e+00	0.00e+00	0.00e+00	0.00e+00	0.00e+00	0.00e+00	5.17e+00	8.05e+00	0.00e+00	0.00e+00	2.79e-02	2.11e-01
chr4	118961578	118968912	ENSMUSG00000024903	49.16	+	Lao1	protein_coding	3.64e-17	2.67e-13	4.729009	2.08e+00	1.83e-03	2.34e+00	5.75e-02	3.17e+00	0.00e+00	3.58e+00	1.58e+00	2.79e-03	0.00e+00	3.84e-03	6.98e-04	0.00e+00	0.00e+00	9.37e+00	0.00e+00	0.00e+00	0.00e+00	2.30e-01	0.00e+00
chr12	113325240	113330523	ENSMUSG00000076614	50.68	-	Ighg1	IG_C_gene	1.02e-16	5.01e-13	-3.048363	6.61e+00	8.12e-02	4.70e+00	9.59e-03	4.70e+00	1.00e+01	4.17e+00	7.55e+00	6.39e-03	2.66e-01	4.35e-03	4.78e-02	4.86e+00	3.58e+00	6.64e+00	3.70e+00	7.16e-03	2.81e-03	2.53e-02	3.07e-03
chr5	137061504	137072268	ENSMUSG00000037411	50.16	-	Serpine1	protein_coding	3.81e-13	1.40e-09	3.093109	5.72e+00	1.32e-02	7.38e+00	1.15e-01	6.07e+00	6.39e+00	5.09e+00	5.32e+00	1.58e-02	1.99e-02	7.90e-03	9.33e-03	5.49e+00	7.90e+00	1.06e+01	5.49e+00	1.05e-02	5.70e-02	3.81e-01	1.05e-02
chr7	114631478	114636357	ENSMUSG00000030669	46.56	-	Calca	protein_coding	5.10e-13	1.50e-09	-1.595105	3.93e+00	4.84e-02	5.18e+00	1.59e-02	2.00e+00	1.00e+00	1.01e+01	2.58e+00	5.11e-04	1.70e-04	1.92e-01	8.51e-04	4.91e+00	4.52e+00	8.31e+00	3.00e+00	4.94e-03	3.74e-03	5.38e-02	1.19e-03
chr3	83040141	83049863	ENSMUSG00000033831	40.98	-	Fgb	protein_coding	1.42e-12	3.26e-09	-2.628559	6.96e+00	8.81e-02	5.29e+00	1.40e-02	7.68e+00	9.70e+00	7.66e+00	2.81e+00	5.80e-02	2.35e-01	5.72e-02	1.71e-03	5.93e+00	3.17e+00	6.17e+00	5.88e+00	1.71e-02	2.28e-03	2.02e-02	1.65e-02
chr1	120474538	120505024	ENSMUSG00000026390	46.94	-	Marco	protein_coding	1.55e-12	3.26e-09	-2.731764	9.26e+00	2.45e-01	6.53e+00	3.66e-02	8.96e+00	9.92e+00	8.76e+00	9.42e+00	1.89e-01	3.68e-01	1.64e-01	2.60e-01	7.19e+00	5.91e+00	6.60e+00	6.43e+00	5.52e-02	2.24e-02	3.65e-02	3.23e-02
chr2	164354070	164389095	ENSMUSG00000017002	45.08	-	Slpi	protein_coding	6.83e-12	1.26e-08	-2.987548	7.13e+00	8.43e-02	4.43e+00	1.04e-02	6.17e+00	1.00e+01	5.73e+00	6.60e+00	1.89e-02	2.79e-01	1.39e-02	2.56e-02	6.67e+00	3.70e+00	5.36e+00	2.00e+00	2.69e-02	3.20e-03	1.07e-02	8.00e-04
chr8	83290352	83298452	ENSMUSG00000031710	43.07	+	Ucp1	protein_coding	8.25e-12	1.35e-08	-4.280108	2.41e+00	3.86e-02	1.58e+00	1.44e-03	8.06e+00	0.00e+00	1.58e+00	0.00e+00	1.53e-01	0.00e+00	1.15e-03	0.00e+00	2.32e+00	2.00e+00	0.00e+00	2.00e+00	2.31e-03	1.73e-03	0.00e+00	1.73e-03
chr11	6635482	6638637	ENSMUSG00000000381	52.44	-	Wap	protein_coding	1.36e-11	2.00e-08	3.574133	3.08e+00	1.34e-02	2.46e+00	1.67e-01	4.91e+00	0.00e+00	5.43e+00	2.00e+00	2.09e-02	0.00e+00	3.03e-02	2.17e-03	0.00e+00	0.00e+00	9.85e+00	0.00e+00	0.00e+00	0.00e+00	6.68e-01	0.00e+00
chr18	43728069	43737237	ENSMUSG00000024503	39.67	-	Spink1	protein_coding	1.52e-11	2.01e-08	-3.404390	2.51e+00	3.27e-02	1.51e+00	2.42e-03	1.00e+00	1.58e+00	7.44e+00	0.00e+00	7.43e-04	1.49e-03	1.29e-01	0.00e+00	1.58e+00	1.00e+00	3.46e+00	0.00e+00	1.49e-03	7.43e-04	7.43e-03	0.00e+00
chr3	87357881	87371073	ENSMUSG00000015854	43.01	+	Cd5l	protein_coding	1.64e-11	2.01e-08	-3.015089	7.61e+00	1.02e-01	4.54e+00	1.22e-02	7.07e+00	8.52e+00	6.94e+00	7.91e+00	6.30e-02	1.73e-01	5.78e-02	1.14e-01	5.70e+00	3.70e+00	4.25e+00	4.52e+00	2.42e-02	5.69e-03	8.53e-03	1.04e-02
chr15	85017141	85022560	ENSMUSG00000022435	53.17	+	Upk3a	protein_coding	3.66e-11	4.14e-08	-2.267104	7.50e+00	2.00e-01	5.64e+00	4.09e-02	8.10e+00	9.23e+00	7.86e+00	4.81e+00	1.93e-01	4.23e-01	1.64e-01	1.91e-02	4.17e+00	6.27e+00	6.52e+00	5.61e+00	1.20e-02	5.36e-02	6.42e-02	3.39e-02
chr11	112782224	112787760	ENSMUSG00000000567	50.95	+	Sox9	protein_coding	7.97e-11	8.37e-08	-1.891851	7.78e+00	8.31e-02	5.93e+00	2.22e-02	7.69e+00	8.54e+00	9.06e+00	5.83e+00	5.88e-02	1.06e-01	1.52e-01	1.60e-02	5.17e+00	5.49e+00	7.55e+00	5.52e+00	9.99e-03	1.26e-02	5.34e-02	1.28e-02
chr4	124986430	125009099	ENSMUSG00000028871	52.35	+	Rspo1	protein_coding	1.10e-10	1.08e-07	-2.532495	5.63e+00	4.38e-02	3.22e+00	7.11e-03	6.21e+00	6.41e+00	7.31e+00	2.58e+00	3.99e-02	4.60e-02	8.64e-02	2.74e-03	2.32e+00	3.00e+00	5.25e+00	2.32e+00	2.19e-03	3.83e-03	2.02e-02	2.19e-03
chr8	106603351	106670246	ENSMUSG00000000303	47.03	+	Cdh1	protein_coding	2.28e-10	2.10e-07	-1.938436	9.40e+00	1.77e-01	7.42e+00	4.60e-02	9.55e+00	9.47e+00	1.01e+01	8.46e+00	1.81e-01	1.72e-01	2.71e-01	8.50e-02	7.13e+00	7.10e+00	8.52e+00	6.92e+00	3.36e-02	3.29e-02	8.87e-02	2.90e-02
chr4	134315120	134329629	ENSMUSG00000028834	49.94	+	Trim63	protein_coding	7.01e-10	6.07e-07	3.515254	3.50e+00	3.80e-03	2.31e+00	4.67e-02	2.58e+00	4.09e+00	4.52e+00	2.81e+00	1.55e-03	4.97e-03	6.83e-03	1.86e-03	0.00e+00	0.00e+00	9.24e+00	0.00e+00	0.00e+00	0.00e+00	1.87e-01	0.00e+00
chr4	120666572	120667820	ENSMUSG00000070803	66.37	+	Cited4	protein_coding	9.79e-10	8.00e-07	-2.273018	6.27e+00	7.34e-02	4.00e+00	1.46e-02	6.79e+00	6.55e+00	7.74e+00	4.00e+00	7.49e-02	6.34e-02	1.45e-01	1.02e-02	4.00e+00	3.91e+00	5.75e+00	2.32e+00	1.02e-02	9.54e-03	3.61e-02	2.72e-03
chr9	98422961	98446575	ENSMUSG00000046402	49.41	+	Rbp1	protein_coding	1.57e-09	1.22e-06	-2.055230	8.66e+00	2.87e-01	6.66e+00	6.86e-02	8.71e+00	8.72e+00	9.27e+00	7.93e+00	2.83e-01	2.84e-01	4.18e-01	1.64e-01	6.69e+00	6.38e+00	7.03e+00	6.54e+00	6.89e-02	5.54e-02	8.78e-02	6.22e-02
chr2	157544266	157545469	ENSMUSG00000087445	45.60	-	Gm14286	antisense	1.75e-09	1.29e-06	2.462180	4.90e+00	2.77e-02	7.58e+00	1.56e-01	5.09e+00	5.93e+00	5.25e+00	3.32e+00	2.63e-02	4.78e-02	2.95e-02	7.18e-03	7.36e+00	7.67e+00	7.22e+00	8.09e+00	1.30e-01	1.61e-01	1.18e-01	2.16e-01
chrX	45090904	45092791	ENSMUSG00000037086	40.41	+	Prr32	protein_coding	2.06e-09	1.44e-06	2.716207	3.69e+00	9.28e-03	5.59e+00	6.50e-02	4.52e+00	3.00e+00	3.32e+00	3.91e+00	1.57e-02	5.00e-03	6.42e-03	9.99e-03	6.44e+00	7.65e+00	2.00e+00	6.25e+00	6.14e-02	1.43e-01	2.14e-03	5.35e-02
chr7	27473768	27477364	ENSMUSG00000055200	51.04	+	Sertad3	protein_coding	2.84e-09	1.90e-06	-2.965472	5.84e+00	3.79e-02	3.18e+00	4.38e-03	5.21e+00	7.14e+00	6.44e+00	4.58e+00	1.91e-02	7.44e-02	4.57e-02	1.22e-02	3.00e+00	3.58e+00	3.32e+00	2.81e+00	3.72e-03	5.84e-03	4.78e-03	3.19e-03
chr13	71957921	71963723	ENSMUSG00000060969	53.46	-	Irx1	protein_coding	2.35e-08	1.50e-05	-1.699552	7.87e+00	1.56e-01	6.26e+00	4.76e-02	8.38e+00	8.45e+00	8.91e+00	5.75e+00	1.70e-01	1.79e-01	2.47e-01	2.72e-02	6.34e+00	5.09e+00	7.62e+00	5.98e+00	4.10e-02	1.69e-02	1.01e-01	3.18e-02
chr18	58008623	58209926	ENSMUSG00000024598	42.14	-	Fbn2	protein_coding	3.09e-08	1.89e-05	-2.552972	5.24e+00	1.90e-02	2.76e+00	2.94e-03	5.25e+00	6.71e+00	6.19e+00	2.81e+00	1.28e-02	3.60e-02	2.49e-02	2.08e-03	2.58e+00	1.00e+00	4.46e+00	3.00e+00	1.73e-03	3.46e-04	7.27e-03	2.42e-03
chr12	111484611	111485823	ENSMUSG00000010529	57.63	-	Gm266	protein_coding	3.81e-08	2.24e-05	-2.302563	5.26e+00	4.69e-02	3.72e+00	9.00e-03	5.67e+00	6.58e+00	7.19e+00	1.58e+00	3.21e-02	6.11e-02	9.32e-02	1.29e-03	3.70e+00	3.32e+00	4.86e+00	3.00e+00	7.71e-03	5.78e-03	1.80e-02	4.50e-03
chr11	115163341	115181181	ENSMUSG00000020733	53.74	+	Slc9a3r1	protein_coding	4.64e-08	2.62e-05	-2.452924	6.90e+00	7.13e-02	4.60e+00	1.26e-02	6.57e+00	6.88e+00	6.04e+00	8.10e+00	4.88e-02	6.07e-02	3.37e-02	1.42e-01	4.46e+00	4.70e+00	5.17e+00	4.09e+00	1.09e-02	1.30e-02	1.82e-02	8.31e-03
chr15	11839896	11905674	ENSMUSG00000022206	42.69	-	Npr3	protein_coding	7.31e-08	3.98e-05	1.810495	7.81e+00	3.50e-02	9.45e+00	1.23e-01	7.99e+00	8.19e+00	7.67e+00	7.38e+00	3.89e-02	4.47e-02	3.11e-02	2.52e-02	9.49e+00	1.04e+01	8.10e+00	9.82e+00	1.10e-01	2.02e-01	4.19e-02	1.38e-01
chr18	34859823	34864984	ENSMUSG00000038418	57.77	+	Egr1	protein_coding	8.10e-08	4.25e-05	1.857647	7.96e+00	1.05e-01	9.71e+00	3.82e-01	8.40e+00	8.19e+00	8.08e+00	7.17e+00	1.36e-01	1.18e-01	1.09e-01	5.79e-02	1.03e+01	8.65e+00	9.39e+00	1.05e+01	5.04e-01	1.62e-01	2.70e-01	5.92e-01
chr9	108953586	108984875	ENSMUSG00000025650	54.80	+	Col7a1	protein_coding	1.31e-07	6.64e-05	-1.721055	6.70e+00	1.61e-02	4.66e+00	4.78e-03	6.30e+00	7.32e+00	7.86e+00	5.32e+00	9.88e-03	2.01e-02	2.93e-02	4.94e-03	4.95e+00	3.70e+00	6.66e+00	3.32e+00	3.80e-03	1.52e-03	1.27e-02	1.14e-03
chr8	24584136	24597009	ENSMUSG00000031551	43.76	-	Ido1	protein_coding	1.94e-07	9.51e-05	2.554589	3.30e+00	7.24e-03	5.48e+00	4.57e-02	2.32e+00	4.58e+00	2.58e+00	3.70e+00	2.63e-03	1.51e-02	3.29e-03	7.89e-03	6.57e+00	4.09e+00	4.00e+00	7.27e+00	6.18e-02	1.05e-02	9.87e-03	1.01e-01
chr11	67171027	67197517	ENSMUSG00000033196	42.63	+	Myh2	protein_coding	2.49e-07	1.18e-04	-2.112894	4.14e+00	1.73e-02	2.85e+00	3.70e-03	2.58e+00	5.29e+00	7.11e+00	1.58e+00	1.90e-03	1.44e-02	5.20e-02	7.58e-04	1.00e+00	2.00e+00	4.32e+00	4.09e+00	3.79e-04	1.14e-03	7.21e-03	6.07e-03
chr9	21835510	21837347	ENSMUSG00000047822	55.22	+	Angptl8	protein_coding	4.05e-07	1.86e-04	-3.080565	5.73e+00	5.10e-02	2.67e+00	5.45e-03	5.25e+00	5.78e+00	4.25e+00	7.65e+00	2.44e-02	3.57e-02	1.19e-02	1.32e-01	3.91e+00	3.46e+00	0.00e+00	3.32e+00	9.25e-03	6.61e-03	0.00e+00	5.94e-03
chr8	94172664	94173568	ENSMUSG00000031762	55.69	+	Mt2	protein_coding	4.80e-07	2.14e-04	2.546066	9.16e+00	4.52e-01	9.79e+00	2.64e+00	8.68e+00	1.01e+01	9.21e+00	8.60e+00	2.92e-01	8.11e-01	4.25e-01	2.78e-01	7.81e+00	8.81e+00	1.37e+01	8.80e+00	1.60e-01	3.21e-01	9.77e+00	3.19e-01
chr7	131032053	131121630	ENSMUSG00000047517	45.50	+	Dmbt1	protein_coding	7.07e-07	3.06e-04	-2.275634	5.19e+00	1.66e-02	3.02e+00	3.23e-03	4.09e+00	7.73e+00	4.95e+00	4.00e+00	3.90e-03	5.14e-02	7.30e-03	3.65e-03	3.91e+00	0.00e+00	5.00e+00	3.17e+00	3.41e-03	0.00e+00	7.55e-03	1.95e-03
chr7	127208890	127214298	ENSMUSG00000030672	50.10	+	Mylpf	protein_coding	7.76e-07	3.18e-04	-1.371172	7.91e+00	1.39e-01	7.11e+00	5.34e-02	6.92e+00	9.00e+00	9.62e+00	6.11e+00	4.48e-02	1.91e-01	2.94e-01	2.54e-02	6.82e+00	6.78e+00	7.79e+00	7.04e+00	4.18e-02	4.07e-02	8.22e-02	4.89e-02
chr2	32384633	32388252	ENSMUSG00000026822	54.70	-	Lcn2	protein_coding	7.78e-07	3.18e-04	-0.997223	8.99e+00	2.22e-01	7.38e+00	1.11e-01	1.10e+01	1.04e+01	1.04e+01	4.25e+00	3.77e-01	2.52e-01	2.57e-01	3.43e-03	6.58e+00	5.58e+00	1.10e+01	6.32e+00	1.81e-02	8.96e-03	4.03e-01	1.51e-02
chr7	28071236	28120862	ENSMUSG00000047730	49.45	+	Fcgbp	protein_coding	9.99e-07	3.97e-04	-1.110032	7.87e+00	2.27e-01	7.47e+00	1.05e-01	9.07e+00	9.32e+00	1.03e+01	2.81e+00	2.02e-01	2.40e-01	4.64e-01	2.25e-03	7.60e+00	5.83e+00	9.56e+00	6.87e+00	7.24e-02	2.10e-02	2.83e-01	4.35e-02
chr4	121039385	121055322	ENSMUSG00000028626	52.07	+	Col9a2	protein_coding	1.07e-06	4.14e-04	-1.481127	4.75e+00	2.17e-02	3.44e+00	7.58e-03	5.61e+00	6.23e+00	7.16e+00	0.00e+00	1.58e-02	2.44e-02	4.68e-02	0.00e+00	2.32e+00	2.00e+00	6.29e+00	3.17e+00	1.32e-03	9.88e-04	2.54e-02	2.64e-03
chr14	54642161	54686931	ENSMUSG00000022185	45.59	-	Acin1	protein_coding	1.13e-06	4.26e-04	-1.729058	7.93e+00	1.43e-02	6.17e+00	4.29e-03	7.51e+00	8.18e+00	7.45e+00	8.58e+00	1.01e-02	1.62e-02	9.72e-03	2.13e-02	5.32e+00	6.02e+00	6.94e+00	6.38e+00	2.18e-03	3.58e-03	6.82e-03	4.58e-03
chr7	19404776	19422841	ENSMUSG00000030399	51.89	+	Ckm	protein_coding	1.30e-06	4.72e-04	-1.136419	6.46e+00	3.33e-02	4.96e+00	1.50e-02	5.61e+00	7.61e+00	8.04e+00	4.58e+00	1.21e-02	4.90e-02	6.64e-02	5.80e-03	3.00e+00	4.25e+00	7.50e+00	5.09e+00	1.77e-03	4.54e-03	4.54e-02	8.33e-03
chr5	125017153	125179219	ENSMUSG00000029478	55.08	-	Ncor2	protein_coding	1.32e-06	4.72e-04	-1.829050	7.63e+00	1.80e-02	5.99e+00	5.00e-03	6.43e+00	7.86e+00	7.43e+00	8.80e+00	6.54e-03	1.78e-02	1.32e-02	3.43e-02	5.52e+00	5.95e+00	6.60e+00	5.88e+00	3.46e-03	4.69e-03	7.38e-03	4.46e-03
chr6	134981718	134986836	ENSMUSG00000090698	47.31	+	Apold1	protein_coding	1.55e-06	5.41e-04	1.955097	5.19e+00	1.00e-02	7.18e+00	3.96e-02	4.52e+00	5.64e+00	4.86e+00	5.73e+00	5.84e-03	1.30e-02	7.44e-03	1.38e-02	6.92e+00	7.32e+00	7.73e+00	6.74e+00	3.19e-02	4.22e-02	5.63e-02	2.82e-02
chr17	24696234	24700529	ENSMUSG00000019320	52.93	+	Noxo1	protein_coding	1.62e-06	5.53e-04	-2.013056	5.43e+00	9.97e-03	3.09e+00	2.33e-03	4.64e+00	5.98e+00	6.85e+00	4.25e+00	4.39e-03	1.13e-02	2.08e-02	3.29e-03	0.00e+00	3.70e+00	4.00e+00	4.64e+00	0.00e+00	2.19e-03	2.74e-03	4.39e-03
chr14	79637690	79662170	ENSMUSG00000022025	44.12	-	Lect1	protein_coding	1.93e-06	6.44e-04	-2.978626	3.96e+00	8.06e-03	1.83e+00	8.06e-04	5.49e+00	4.25e+00	6.11e+00	0.00e+00	1.09e-02	4.46e-03	1.69e-02	0.00e+00	2.32e+00	1.00e+00	1.00e+00	3.00e+00	9.92e-04	2.48e-04	2.48e-04	1.74e-03
chr10	111506286	111508645	ENSMUSG00000020205	58.05	+	Phlda1	protein_coding	2.20e-06	7.18e-04	-1.372087	7.25e+00	6.83e-02	5.91e+00	2.61e-02	7.23e+00	7.12e+00	8.48e+00	6.17e+00	5.71e-02	5.29e-02	1.36e-01	2.72e-02	5.46e+00	5.36e+00	7.14e+00	5.67e+00	1.65e-02	1.53e-02	5.36e-02	1.92e-02
chr19	5664635	5688908	ENSMUSG00000054874	55.20	-	Pcnx3	protein_coding	3.27e-06	1.04e-03	-1.945960	6.58e+00	8.80e-03	4.47e+00	2.22e-03	6.21e+00	6.88e+00	6.27e+00	6.95e+00	6.60e-03	1.06e-02	6.88e-03	1.11e-02	4.00e+00	4.70e+00	5.58e+00	3.58e+00	1.36e-03	2.26e-03	4.25e-03	9.95e-04
chr2	103263433	103303278	ENSMUSG00000012350	44.33	-	Ehf	protein_coding	3.61e-06	1.13e-03	-1.382470	5.61e+00	7.49e-03	3.94e+00	2.81e-03	5.98e+00	6.00e+00	7.29e+00	3.17e+00	6.45e-03	6.56e-03	1.61e-02	8.33e-04	2.58e+00	3.46e+00	6.41e+00	3.32e+00	5.20e-04	1.04e-03	8.74e-03	9.37e-04
chr4	118432901	118437352	ENSMUSG00000006398	50.97	-	Cdc20	protein_coding	4.23e-06	1.29e-03	-2.469485	5.64e+00	1.39e-02	3.04e+00	2.29e-03	4.75e+00	5.52e+00	6.34e+00	5.95e+00	6.80e-03	1.18e-02	2.09e-02	1.60e-02	3.17e+00	4.09e+00	3.32e+00	1.58e+00	2.09e-03	4.19e-03	2.35e-03	5.23e-04
chr15	74762056	74763620	ENSMUSG00000034634	52.08	-	Ly6d	protein_coding	4.41e-06	1.30e-03	-1.694160	9.30e+00	4.14e-01	7.62e+00	1.28e-01	8.92e+00	9.57e+00	9.05e+00	9.65e+00	3.10e-01	4.88e-01	3.41e-01	5.17e-01	7.62e+00	7.97e+00	7.40e+00	7.50e+00	1.26e-01	1.60e-01	1.08e-01	1.16e-01
chr10	93583029	93589706	ENSMUSG00000020018	42.02	-	Snrpf	protein_coding	4.41e-06	1.30e-03	-2.330645	6.22e+00	4.85e-02	4.00e+00	9.18e-03	5.88e+00	6.70e+00	5.29e+00	7.02e+00	3.43e-02	6.10e-02	2.25e-02	7.64e-02	3.70e+00	4.52e+00	3.70e+00	4.09e+00	7.10e-03	1.30e-02	7.10e-03	9.47e-03
chr7	19689481	19692660	ENSMUSG00000040564	52.26	-	Apoc1	protein_coding	4.76e-06	1.37e-03	-1.468224	9.28e+00	2.42e-01	7.79e+00	8.72e-02	9.51e+00	9.45e+00	9.46e+00	8.71e+00	2.76e-01	2.66e-01	2.67e-01	1.59e-01	7.19e+00	8.16e+00	8.17e+00	7.64e+00	5.51e-02	1.09e-01	1.09e-01	7.56e-02
chr15	78191114	78206400	ENSMUSG00000005716	52.25	-	Pvalb	protein_coding	5.97e-06	1.69e-03	-1.169925	6.31e+00	8.17e-02	5.61e+00	3.60e-02	5.04e+00	8.15e+00	8.02e+00	4.00e+00	1.77e-02	1.57e-01	1.43e-01	8.31e-03	4.09e+00	5.25e+00	7.24e+00	5.86e+00	8.86e-03	2.05e-02	8.31e-02	3.16e-02
chr11	70315610	70322628	ENSMUSG00000018907	51.67	-	Alox12e	protein_coding	7.40e-06	2.05e-03	-0.901560	5.27e+00	2.66e-02	4.16e+00	1.41e-02	7.00e+00	6.19e+00	7.89e+00	0.00e+00	3.11e-02	1.76e-02	5.78e-02	0.00e+00	3.00e+00	2.32e+00	7.71e+00	3.58e+00	1.71e-03	9.79e-04	5.12e-02	2.69e-03
chr6	121300227	121337733	ENSMUSG00000030108	47.71	+	Slc6a13	protein_coding	7.67e-06	2.06e-03	1.868602	4.72e+00	5.06e-03	6.46e+00	1.90e-02	4.17e+00	5.49e+00	4.75e+00	4.46e+00	3.19e-03	8.25e-03	4.88e-03	3.94e-03	7.10e+00	7.24e+00	5.04e+00	6.46e+00	2.55e-02	2.81e-02	6.00e-03	1.63e-02
chr7	6703892	6730431	ENSMUSG00000002265	44.95	-	Peg3	protein_coding	7.71e-06	2.06e-03	2.095875	6.96e+00	9.86e-03	7.85e+00	4.24e-02	6.99e+00	6.86e+00	7.50e+00	6.48e+00	9.76e-03	8.91e-03	1.39e-02	6.82e-03	7.04e+00	6.98e+00	1.08e+01	6.52e+00	1.01e-02	9.68e-03	1.43e-01	7.05e-03
chr9	102716672	102733418	ENSMUSG00000032531	52.92	+	Amotl2	protein_coding	8.86e-06	2.29e-03	1.589209	8.65e+00	4.52e-02	1.03e+01	1.36e-01	9.23e+00	8.72e+00	8.79e+00	7.86e+00	6.41e-02	4.49e-02	4.71e-02	2.47e-02	1.03e+01	1.03e+01	1.04e+01	1.03e+01	1.33e-01	1.35e-01	1.42e-01	1.35e-01
chr5	87774567	87788797	ENSMUSG00000061937	33.49	+	Csn1s2a	protein_coding	8.87e-06	2.29e-03	2.510078	8.00e+00	8.65e-02	5.72e+00	4.94e-01	1.04e+01	7.25e+00	1.02e+01	4.17e+00	1.69e-01	1.94e-02	1.55e-01	2.19e-03	1.00e+00	4.09e+00	1.39e+01	3.91e+00	1.29e-04	2.06e-03	1.97e+00	1.80e-03
chr1	83116766	83119167	ENSMUSG00000026166	39.26	+	Ccl20	protein_coding	9.55e-06	2.42e-03	-3.129283	3.15e+00	7.16e-03	7.50e-01	4.34e-04	3.00e+00	4.17e+00	5.43e+00	0.00e+00	3.04e-03	7.38e-03	1.82e-02	0.00e+00	0.00e+00	1.00e+00	2.00e+00	0.00e+00	0.00e+00	4.34e-04	1.30e-03	0.00e+00
chr7	31068172	31076704	ENSMUSG00000057092	51.79	-	Fxyd3	protein_coding	9.87e-06	2.46e-03	-1.116951	7.83e+00	3.68e-02	6.65e+00	1.69e-02	7.97e+00	8.66e+00	8.73e+00	5.95e+00	3.23e-02	5.21e-02	5.50e-02	7.89e-03	5.78e+00	6.48e+00	8.31e+00	6.02e+00	6.99e-03	1.14e-02	4.10e-02	8.28e-03
chr15	101266846	101274792	ENSMUSG00000023034	55.61	+	Nr4a1	protein_coding	1.04e-05	2.54e-03	1.742243	5.54e+00	2.61e-02	7.29e+00	8.85e-02	5.98e+00	5.46e+00	5.04e+00	5.67e+00	3.46e-02	2.40e-02	1.78e-02	2.79e-02	7.17e+00	7.01e+00	7.73e+00	7.27e+00	7.97e-02	7.13e-02	1.18e-01	8.53e-02
chr1	193507238	193510174	ENSMUSG00000097850	48.14	-	4631405K08Rik	lincRNA	1.07e-05	2.57e-03	-2.137504	4.49e+00	3.87e-02	3.30e+00	8.17e-03	5.55e+00	5.93e+00	6.48e+00	0.00e+00	3.67e-02	4.78e-02	7.02e-02	0.00e+00	3.81e+00	2.81e+00	4.25e+00	2.32e+00	1.04e-02	4.78e-03	1.44e-02	3.19e-03
chr4	140700541	140723220	ENSMUSG00000040945	55.18	+	Rcc2	protein_coding	1.11e-05	2.63e-03	-1.643196	8.40e+00	5.80e-02	6.77e+00	1.84e-02	8.29e+00	8.50e+00	8.10e+00	8.70e+00	5.33e-02	6.13e-02	4.67e-02	7.05e-02	6.69e+00	6.87e+00	6.82e+00	6.70e+00	1.74e-02	1.98e-02	1.91e-02	1.75e-02
chr5	34525838	34563641	ENSMUSG00000054520	51.68	+	Sh3bp2	protein_coding	1.13e-05	2.63e-03	-1.863498	7.30e+00	2.20e-02	5.46e+00	5.94e-03	7.38e+00	6.61e+00	7.43e+00	7.77e+00	2.23e-02	1.31e-02	2.32e-02	2.93e-02	5.83e+00	5.64e+00	5.36e+00	5.00e+00	7.56e-03	6.62e-03	5.40e-03	4.19e-03
chr17	70844205	70853546	ENSMUSG00000047407	49.06	-	Tgif1	protein_coding	1.31e-05	2.97e-03	-1.670936	7.21e+00	2.41e-02	5.51e+00	7.46e-03	7.41e+00	7.48e+00	7.26e+00	6.69e+00	2.71e-02	2.86e-02	2.44e-02	1.64e-02	5.64e+00	5.29e+00	6.11e+00	5.00e+00	7.86e-03	6.10e-03	1.09e-02	4.97e-03
chr8	3917655	3926844	ENSMUSG00000065987	44.68	-	Cd209b	protein_coding	1.31e-05	2.97e-03	-1.564869	8.41e+00	1.01e-01	6.83e+00	3.40e-02	8.43e+00	9.11e+00	7.94e+00	8.14e+00	9.79e-02	1.57e-01	6.95e-02	8.00e-02	6.92e+00	6.00e+00	7.03e+00	7.38e+00	3.42e-02	1.79e-02	3.70e-02	4.70e-02
chr15	78877190	78894585	ENSMUSG00000033128	56.17	+	Gga1	protein_coding	1.35e-05	2.99e-03	-1.666159	7.07e+00	7.51e-02	5.38e+00	2.33e-02	6.46e+00	7.49e+00	6.34e+00	7.99e+00	4.36e-02	8.97e-02	4.01e-02	1.27e-01	4.39e+00	5.73e+00	6.39e+00	5.00e+00	1.00e-02	2.61e-02	4.16e-02	1.55e-02
chr11	106263179	106272972	ENSMUSG00000078619	52.24	-	Smarcd2	protein_coding	1.36e-05	2.99e-03	-1.378127	9.54e+00	1.03e-01	8.08e+00	3.96e-02	9.30e+00	9.82e+00	9.53e+00	9.51e+00	8.66e-02	1.25e-01	1.02e-01	1.00e-01	7.66e+00	8.15e+00	8.87e+00	7.64e+00	2.77e-02	3.90e-02	6.43e-02	2.74e-02
chr19	3935186	3949340	ENSMUSG00000036908	48.75	+	Unc93b1	protein_coding	1.41e-05	3.05e-03	-1.612926	8.64e+00	9.85e-02	7.08e+00	3.20e-02	8.39e+00	9.18e+00	8.06e+00	8.92e+00	7.91e-02	1.37e-01	6.28e-02	1.15e-01	7.12e+00	7.02e+00	7.31e+00	6.87e+00	3.27e-02	3.06e-02	3.74e-02	2.75e-02
chr3	121723537	121735048	ENSMUSG00000028128	45.60	+	F3	protein_coding	1.60e-05	3.42e-03	1.576531	6.13e+00	1.54e-02	7.61e+00	4.64e-02	5.83e+00	6.58e+00	5.88e+00	6.21e+00	1.23e-02	2.08e-02	1.27e-02	1.60e-02	7.34e+00	8.25e+00	6.73e+00	8.13e+00	3.52e-02	6.65e-02	2.30e-02	6.10e-02
chr3	116918258	116968987	ENSMUSG00000033377	41.86	-	Palmd	protein_coding	1.69e-05	3.51e-03	1.667177	6.30e+00	1.20e-02	7.95e+00	3.84e-02	6.66e+00	6.04e+00	6.60e+00	5.91e+00	1.50e-02	9.73e-03	1.44e-02	8.83e-03	7.35e+00	8.47e+00	8.06e+00	7.94e+00	2.42e-02	5.28e-02	3.98e-02	3.65e-02
chr13	34127008	34130354	ENSMUSG00000045136	51.06	-	Tubb2b	protein_coding	1.70e-05	3.51e-03	-1.620204	8.00e+00	1.50e-01	6.38e+00	4.85e-02	7.97e+00	7.99e+00	7.70e+00	8.33e+00	1.46e-01	1.48e-01	1.21e-01	1.87e-01	6.36e+00	6.21e+00	6.77e+00	6.17e+00	4.72e-02	4.25e-02	6.29e-02	4.14e-02
chr11	100368958	100397763	ENSMUSG00000001552	52.25	-	Jup	protein_coding	1.75e-05	3.55e-03	-1.558490	7.65e+00	2.78e-02	6.05e+00	9.34e-03	7.56e+00	7.41e+00	7.88e+00	7.75e+00	2.59e-02	2.33e-02	3.23e-02	2.97e-02	5.67e+00	6.49e+00	6.39e+00	5.64e+00	6.90e-03	1.23e-02	1.14e-02	6.76e-03
chr9	31846044	31913462	ENSMUSG00000032033	43.78	-	Barx2	protein_coding	1.78e-05	3.55e-03	-1.713119	4.28e+00	2.45e-02	3.47e+00	7.13e-03	4.46e+00	5.70e+00	6.97e+00	0.00e+00	1.05e-02	2.55e-02	6.20e-02	0.00e+00	3.81e+00	2.58e+00	5.17e+00	2.32e+00	6.50e-03	2.50e-03	1.75e-02	2.00e-03
chr15	75108158	75111970	ENSMUSG00000022584	48.81	-	Ly6c2	protein_coding	1.78e-05	3.55e-03	-1.813549	7.88e+00	1.77e-01	6.30e+00	5.00e-02	7.34e+00	8.05e+00	6.83e+00	9.29e+00	9.82e-02	1.61e-01	6.89e-02	3.81e-01	6.52e+00	5.67e+00	6.11e+00	6.91e+00	5.55e-02	3.05e-02	4.15e-02	7.26e-02
chr15	50654752	50890463	ENSMUSG00000038679	36.69	-	Trps1	protein_coding	2.24e-05	4.37e-03	-1.302729	8.12e+00	2.35e-02	6.78e+00	9.48e-03	7.52e+00	8.17e+00	8.70e+00	8.07e+00	1.48e-02	2.35e-02	3.38e-02	2.19e-02	6.46e+00	6.43e+00	7.64e+00	6.58e+00	7.09e-03	6.93e-03	1.61e-02	7.75e-03
chr8	94772009	94782427	ENSMUSG00000031778	52.68	+	Cx3cl1	protein_coding	2.27e-05	4.37e-03	-1.385431	7.10e+00	1.60e-02	5.74e+00	6.06e-03	7.61e+00	7.69e+00	7.46e+00	5.64e+00	1.99e-02	2.10e-02	1.80e-02	5.03e-03	5.36e+00	5.13e+00	6.82e+00	5.67e+00	4.11e-03	3.49e-03	1.15e-02	5.13e-03
chr16	30599723	30602797	ENSMUSG00000046546	57.72	+	Fam43a	protein_coding	2.29e-05	4.37e-03	-1.708265	7.26e+00	8.36e-02	5.59e+00	2.52e-02	7.52e+00	7.61e+00	6.39e+00	7.52e+00	9.47e-02	1.01e-01	4.32e-02	9.52e-02	5.00e+00	5.91e+00	5.73e+00	5.73e+00	1.61e-02	3.07e-02	2.71e-02	2.71e-02
chr11	59963181	59964944	ENSMUSG00000049892	53.80	-	Rasd1	protein_coding	2.65e-05	5.00e-03	1.427970	7.69e+00	1.25e-01	9.20e+00	3.37e-01	7.86e+00	8.43e+00	8.17e+00	6.29e+00	1.23e-01	1.83e-01	1.52e-01	4.09e-02	9.82e+00	9.37e+00	8.19e+00	9.42e+00	4.78e-01	3.50e-01	1.55e-01	3.63e-01
chr5	7960457	7982213	ENSMUSG00000012428	40.35	+	Steap4	protein_coding	2.84e-05	5.19e-03	1.289423	8.52e+00	1.35e-01	9.75e+00	3.30e-01	9.16e+00	8.86e+00	7.77e+00	8.30e+00	1.96e-01	1.60e-01	7.49e-02	1.08e-01	1.02e+01	1.03e+01	8.45e+00	1.00e+01	4.00e-01	4.39e-01	1.20e-01	3.60e-01
chr15	79154913	79164490	ENSMUSG00000033006	57.69	-	Sox10	protein_coding	2.84e-05	5.19e-03	-0.978569	7.04e+00	8.02e-02	5.94e+00	4.05e-02	7.55e+00	7.60e+00	8.36e+00	4.64e+00	8.16e-02	8.47e-02	1.44e-01	1.05e-02	5.36e+00	5.36e+00	8.01e+00	5.04e+00	1.76e-02	1.76e-02	1.13e-01	1.40e-02
chr8	94179082	94180327	ENSMUSG00000031765	54.25	+	Mt1	protein_coding	2.86e-05	5.19e-03	2.253703	1.03e+01	6.05e-01	1.11e+01	2.89e+00	1.00e+01	1.08e+01	1.03e+01	1.01e+01	4.80e-01	8.38e-01	5.94e-01	5.06e-01	9.53e+00	1.04e+01	1.44e+01	9.95e+00	3.41e-01	6.38e-01	1.01e+01	4.57e-01
chr16	22381309	22439719	ENSMUSG00000013089	46.37	-	Etv5	protein_coding	3.04e-05	5.45e-03	-1.362108	7.76e+00	3.09e-02	6.37e+00	1.19e-02	7.82e+00	7.94e+00	8.09e+00	7.21e+00	3.13e-02	3.40e-02	3.77e-02	2.04e-02	5.98e+00	6.30e+00	7.10e+00	6.09e+00	8.62e-03	1.08e-02	1.89e-02	9.31e-03
chr4	156165290	156197488	ENSMUSG00000041936	53.65	-	Agrn	protein_coding	3.11e-05	5.51e-03	-1.434403	7.16e+00	4.01e-02	5.72e+00	1.47e-02	7.21e+00	7.15e+00	7.78e+00	6.49e+00	3.96e-02	3.80e-02	5.90e-02	2.40e-02	5.61e+00	5.55e+00	6.46e+00	5.25e+00	1.29e-02	1.24e-02	2.34e-02	9.96e-03
chr2	30185124	30205847	ENSMUSG00000039648	49.22	-	Kyat1	protein_coding	3.28e-05	5.74e-03	-1.447295	7.63e+00	6.88e-02	6.04e+00	2.50e-02	7.36e+00	7.77e+00	7.48e+00	7.90e+00	5.64e-02	7.51e-02	6.13e-02	8.24e-02	5.46e+00	6.29e+00	7.01e+00	5.39e+00	1.49e-02	2.67e-02	4.43e-02	1.42e-02
chr1	43730602	43742578	ENSMUSG00000026051	43.81	+	1500015O10Rik	protein_coding	3.33e-05	5.74e-03	-1.878159	5.77e+00	4.51e-02	4.08e+00	1.17e-02	5.75e+00	6.78e+00	6.29e+00	4.25e+00	3.72e-02	7.64e-02	5.40e-02	1.26e-02	3.58e+00	4.52e+00	4.52e+00	3.70e+00	7.71e-03	1.54e-02	1.54e-02	8.42e-03
chr1	128588199	128592293	ENSMUSG00000045382	48.64	-	Cxcr4	protein_coding	3.36e-05	5.74e-03	-1.634716	7.38e+00	5.58e-02	5.80e+00	1.78e-02	8.09e+00	6.95e+00	6.85e+00	7.62e+00	8.60e-02	3.90e-02	3.62e-02	6.22e-02	5.61e+00	5.55e+00	6.30e+00	5.73e+00	1.52e-02	1.46e-02	2.47e-02	1.65e-02
chr6	5483351	5496309	ENSMUSG00000019577	40.66	-	Pdk4	protein_coding	4.07e-05	6.87e-03	2.108879	4.79e+00	4.86e-03	6.17e+00	2.15e-02	5.55e+00	4.91e+00	4.46e+00	4.25e+00	7.85e-03	4.95e-03	3.58e-03	3.07e-03	4.75e+00	5.67e+00	8.57e+00	5.70e+00	4.44e-03	8.53e-03	6.45e-02	8.70e-03
chr19	5795690	5802672	ENSMUSG00000092341	42.49	-	Malat1	lincRNA	4.48e-05	7.48e-03	-1.671009	8.55e+00	2.56e-01	7.67e+00	8.02e-02	7.29e+00	7.73e+00	8.29e+00	1.09e+01	6.10e-02	8.35e-02	1.22e-01	7.59e-01	7.55e+00	7.69e+00	7.91e+00	7.52e+00	7.37e-02	8.11e-02	9.41e-02	7.21e-02
chr19	6938069	6942450	ENSMUSG00000024958	59.15	-	Gpr137	protein_coding	4.78e-05	7.80e-03	-1.808859	6.83e+00	7.65e-02	5.00e+00	2.14e-02	6.04e+00	7.18e+00	6.85e+00	7.27e+00	4.18e-02	9.26e-02	7.33e-02	9.84e-02	5.04e+00	5.81e+00	4.64e+00	4.52e+00	2.06e-02	3.54e-02	1.54e-02	1.41e-02
chr3	114030540	114220718	ENSMUSG00000027966	35.21	+	Col11a1	protein_coding	4.81e-05	7.80e-03	-3.301170	3.28e+00	9.47e-04	7.50e-01	4.37e-05	5.21e+00	4.09e+00	3.81e+00	0.00e+00	2.10e-03	9.32e-04	7.57e-04	0.00e+00	0.00e+00	1.00e+00	1.00e+00	1.00e+00	0.00e+00	5.83e-05	5.83e-05	5.83e-05
chr6	83742990	83758855	ENSMUSG00000006269	52.92	+	Atp6v1b1	protein_coding	4.83e-05	7.80e-03	-1.010921	5.80e+00	2.06e-02	5.56e+00	1.02e-02	7.83e+00	7.24e+00	8.14e+00	0.00e+00	2.84e-02	1.88e-02	3.53e-02	0.00e+00	5.70e+00	3.17e+00	7.77e+00	5.61e+00	6.38e-03	1.00e-03	2.73e-02	6.00e-03
chr2	164777161	164779967	ENSMUSG00000017300	54.26	-	Tnnc2	protein_coding	5.09e-05	8.14e-03	-0.807582	9.87e+00	6.00e-01	9.33e+00	3.43e-01	9.15e+00	1.13e+01	1.16e+01	7.44e+00	2.14e-01	9.24e-01	1.20e+00	6.53e-02	8.00e+00	8.80e+00	1.11e+01	9.38e+00	9.63e-02	1.68e-01	8.57e-01	2.51e-01
chr4	130047840	130099283	ENSMUSG00000040690	54.17	+	Col16a1	protein_coding	5.35e-05	8.46e-03	-1.136137	7.34e+00	6.32e-03	6.42e+00	2.86e-03	7.59e+00	8.08e+00	8.42e+00	5.29e+00	5.77e-03	8.09e-03	1.03e-02	1.14e-03	6.13e+00	5.83e+00	7.52e+00	6.19e+00	2.08e-03	1.68e-03	5.50e-03	2.17e-03
chr6	122819914	122845366	ENSMUSG00000003154	49.31	+	Foxj2	protein_coding	5.41e-05	8.46e-03	-1.599097	7.45e+00	3.55e-02	5.87e+00	1.16e-02	7.55e+00	7.90e+00	7.08e+00	7.29e+00	3.70e-02	4.74e-02	2.67e-02	3.11e-02	5.81e+00	6.19e+00	5.93e+00	5.55e+00	1.10e-02	1.43e-02	1.19e-02	9.16e-03
chr17	25099570	25115967	ENSMUSG00000024170	52.54	-	Telo2	protein_coding	5.57e-05	8.62e-03	-1.782643	6.79e+00	1.53e-02	5.14e+00	4.36e-03	6.55e+00	6.81e+00	6.00e+00	7.79e+00	1.17e-02	1.39e-02	7.91e-03	2.78e-02	5.00e+00	4.81e+00	5.46e+00	5.29e+00	3.89e-03	3.39e-03	5.40e-03	4.77e-03
chr11	98383811	98384953	ENSMUSG00000007877	60.37	+	Tcap	protein_coding	6.00e-05	9.19e-03	-1.215013	4.66e+00	2.87e-02	3.57e+00	1.20e-02	4.52e+00	5.64e+00	6.89e+00	1.58e+00	1.32e-02	2.95e-02	7.10e-02	1.20e-03	2.32e+00	2.32e+00	5.93e+00	3.70e+00	2.41e-03	2.41e-03	3.61e-02	7.22e-03
chr11	112663927	112781976	ENSMUSG00000041674	45.38	-	BC006965	processed_transcript	6.39e-05	9.69e-03	-0.953607	7.05e+00	1.75e-02	6.30e+00	9.00e-03	7.66e+00	7.70e+00	8.95e+00	3.91e+00	1.54e-02	1.58e-02	3.77e-02	1.07e-03	6.73e+00	4.75e+00	8.21e+00	5.49e+00	8.04e-03	1.99e-03	2.26e-02	3.37e-03
chr7	141461094	141466613	ENSMUSG00000048200	57.63	+	Cracr2b	protein_coding	6.46e-05	9.70e-03	-1.036082	8.37e+00	5.97e-02	7.09e+00	2.90e-02	8.69e+00	8.38e+00	8.96e+00	7.44e+00	6.95e-02	5.60e-02	8.42e-02	2.93e-02	6.48e+00	7.04e+00	8.63e+00	6.21e+00	1.49e-02	2.22e-02	6.68e-02	1.23e-02
chr2	172549593	172558622	ENSMUSG00000028640	52.03	+	Tfap2c	protein_coding	6.71e-05	9.97e-03	-0.933314	8.78e+00	1.63e-01	7.99e+00	8.52e-02	9.28e+00	9.53e+00	9.98e+00	6.34e+00	1.66e-01	1.97e-01	2.68e-01	2.13e-02	7.79e+00	6.97e+00	9.51e+00	7.70e+00	5.86e-02	3.30e-02	1.94e-01	5.51e-02
chr4	154983115	155056784	ENSMUSG00000029055	54.74	-	Plch2	protein_coding	6.95e-05	1.02e-02	-1.751321	5.50e+00	5.49e-03	3.67e+00	1.55e-03	5.04e+00	6.07e+00	6.29e+00	4.58e+00	3.55e-03	7.32e-03	8.54e-03	2.55e-03	3.58e+00	2.81e+00	4.95e+00	3.32e+00	1.22e-03	6.65e-04	3.33e-03	9.98e-04
chr19	42197971	42202252	ENSMUSG00000018822	55.58	-	Sfrp5	protein_coding	7.15e-05	1.04e-02	1.647247	5.55e+00	2.54e-02	7.19e+00	8.07e-02	5.13e+00	5.25e+00	6.52e+00	5.29e+00	1.73e-02	1.88e-02	4.62e-02	1.93e-02	7.18e+00	8.15e+00	6.85e+00	6.57e+00	7.32e-02	1.44e-01	5.79e-02	4.78e-02
chr7	105480083	105482300	ENSMUSG00000037060	56.27	-	Prkcdbp	protein_coding	7.55e-05	1.09e-02	1.250164	9.06e+00	2.76e-01	1.01e+01	6.58e-01	9.63e+00	8.99e+00	8.97e+00	8.64e+00	3.99e-01	2.54e-01	2.52e-01	2.00e-01	1.08e+01	1.09e+01	8.41e+00	1.01e+01	9.10e-01	9.86e-01	1.70e-01	5.64e-01
chr11	5106265	5152257	ENSMUSG00000034164	51.25	-	Emid1	protein_coding	7.70e-05	1.10e-02	-1.957440	5.21e+00	5.25e-03	2.61e+00	1.26e-03	6.30e+00	5.21e+00	4.58e+00	4.75e+00	1.01e-02	4.64e-03	2.96e-03	3.35e-03	0.00e+00	2.00e+00	4.00e+00	4.46e+00	0.00e+00	3.87e-04	1.93e-03	2.71e-03
chr1	84036296	84364180	ENSMUSG00000045658	41.17	-	Pid1	protein_coding	8.02e-05	1.13e-02	1.465375	9.65e+00	6.55e-02	1.11e+01	1.81e-01	9.73e+00	9.67e+00	1.00e+01	9.16e+00	6.78e-02	6.52e-02	8.32e-02	4.58e-02	1.14e+01	1.11e+01	1.09e+01	1.11e+01	2.18e-01	1.77e-01	1.49e-01	1.80e-01
chr7	126370060	126377450	ENSMUSG00000030741	55.03	-	Spns1	protein_coding	8.50e-05	1.19e-02	-1.367136	7.70e+00	1.39e-02	6.20e+00	5.33e-03	7.42e+00	7.83e+00	7.36e+00	8.21e+00	1.10e-02	1.47e-02	1.06e-02	1.92e-02	6.04e+00	5.70e+00	7.35e+00	5.70e+00	4.21e-03	3.31e-03	1.05e-02	3.31e-03
chr19	6975048	6977324	ENSMUSG00000056612	60.04	+	Ppp1r14b	protein_coding	8.59e-05	1.19e-02	-1.513032	7.58e+00	1.31e-01	6.10e+00	4.53e-02	7.43e+00	7.33e+00	7.29e+00	8.29e+00	1.13e-01	1.05e-01	1.01e-01	2.04e-01	5.55e+00	6.43e+00	6.36e+00	6.04e+00	3.01e-02	5.56e-02	5.30e-02	4.25e-02
chr3	87930314	87940686	ENSMUSG00000048039	46.66	+	Isg20l2	protein_coding	9.03e-05	1.24e-02	-1.953541	6.04e+00	2.62e-02	4.08e+00	6.47e-03	6.43e+00	6.46e+00	5.39e+00	5.88e+00	3.28e-02	3.36e-02	1.58e-02	2.24e-02	3.91e+00	3.81e+00	3.81e+00	4.81e+00	5.41e-03	5.02e-03	5.02e-03	1.04e-02
chr15	100353200	100361840	ENSMUSG00000056487	44.47	+	Mettl7a2	protein_coding	9.68e-05	1.32e-02	1.710173	4.93e+00	1.31e-02	6.64e+00	4.39e-02	5.39e+00	4.58e+00	4.81e+00	4.95e+00	1.78e-02	9.96e-03	1.17e-02	1.30e-02	6.57e+00	6.48e+00	7.16e+00	6.36e+00	4.07e-02	3.81e-02	6.15e-02	3.51e-02
chr10	4266380	4359470	ENSMUSG00000038587	45.53	+	Akap12	protein_coding	1.00e-04	1.36e-02	1.313834	8.13e+00	8.76e-02	9.46e+00	2.18e-01	8.58e+00	7.77e+00	8.23e+00	7.92e+00	1.18e-01	6.67e-02	9.19e-02	7.41e-02	9.53e+00	9.68e+00	9.26e+00	9.39e+00	2.27e-01	2.53e-01	1.88e-01	2.06e-01
chr10	86690209	86705509	ENSMUSG00000020048	42.75	-	Hsp90b1	protein_coding	1.02e-04	1.36e-02	-1.502085	1.03e+01	1.99e-01	8.82e+00	7.02e-02	1.06e+01	1.06e+01	9.81e+00	1.03e+01	2.31e-01	2.36e-01	1.37e-01	1.93e-01	9.16e+00	8.89e+00	8.86e+00	8.35e+00	8.76e-02	7.26e-02	7.09e-02	4.99e-02
chr4	147940895	147947314	ENSMUSG00000044496	54.08	+	2510039O18Rik	protein_coding	1.02e-04	1.36e-02	-1.349267	7.75e+00	1.12e-01	6.32e+00	4.37e-02	7.54e+00	8.17e+00	7.38e+00	7.89e+00	9.49e-02	1.47e-01	8.51e-02	1.22e-01	5.39e+00	6.69e+00	6.93e+00	6.29e+00	2.10e-02	5.23e-02	6.21e-02	3.95e-02
chr7	27179742	27181157	ENSMUSG00000089661	48.87	-	Mia	protein_coding	1.05e-04	1.37e-02	-1.150622	6.48e+00	4.46e-02	4.68e+00	1.99e-02	6.74e+00	7.07e+00	7.65e+00	4.46e+00	4.11e-02	5.16e-02	7.76e-02	8.15e-03	5.52e+00	4.52e+00	7.10e+00	1.58e+00	1.75e-02	8.54e-03	5.28e-02	7.76e-04
chr7	126491708	126503437	ENSMUSG00000032637	51.38	-	Atxn2l	protein_coding	1.06e-04	1.38e-02	1.962938	3.96e+00	3.44e-03	5.86e+00	1.40e-02	4.00e+00	4.64e+00	2.81e+00	4.39e+00	3.18e-03	5.08e-03	1.27e-03	4.23e-03	4.81e+00	5.43e+00	6.29e+00	6.91e+00	5.72e-03	8.89e-03	1.63e-02	2.52e-02
chr1	172209894	172219868	ENSMUSG00000007122	49.55	-	Casq1	protein_coding	1.08e-04	1.38e-02	-2.097611	4.22e+00	8.70e-03	2.18e+00	1.77e-03	4.00e+00	5.32e+00	5.55e+00	2.00e+00	5.07e-03	1.32e-02	1.55e-02	1.01e-03	0.00e+00	2.32e+00	2.81e+00	3.58e+00	0.00e+00	1.35e-03	2.03e-03	3.72e-03
chr7	127925716	127930104	ENSMUSG00000030800	54.55	-	Prss8	protein_coding	1.09e-04	1.38e-02	-1.681824	5.18e+00	8.31e-03	2.90e+00	2.44e-03	4.75e+00	5.29e+00	5.93e+00	4.75e+00	5.76e-03	8.43e-03	1.33e-02	5.76e-03	2.32e+00	3.32e+00	4.95e+00	1.00e+00	8.87e-04	2.00e-03	6.65e-03	2.22e-04
chr5	92331827	92414628	ENSMUSG00000034842	44.88	+	Art3	protein_coding	1.09e-04	1.38e-02	1.338343	7.63e+00	3.50e-02	8.90e+00	8.87e-02	7.81e+00	7.89e+00	7.63e+00	7.18e+00	3.90e-02	4.13e-02	3.45e-02	2.52e-02	8.67e+00	9.38e+00	8.17e+00	9.39e+00	7.10e-02	1.16e-01	5.04e-02	1.17e-01
chr10	79910053	79917006	ENSMUSG00000035781	56.15	-	R3hdm4	protein_coding	1.10e-04	1.38e-02	-1.424385	8.34e+00	1.49e-01	6.95e+00	5.54e-02	8.14e+00	8.37e+00	7.95e+00	8.91e+00	1.26e-01	1.47e-01	1.10e-01	2.15e-01	6.63e+00	7.04e+00	7.24e+00	6.88e+00	4.37e-02	5.85e-02	6.70e-02	5.22e-02
chr19	58795751	58860984	ENSMUSG00000025092	49.21	-	Hspa12a	protein_coding	1.13e-04	1.41e-02	1.291114	7.03e+00	2.70e-02	8.12e+00	6.65e-02	7.03e+00	6.70e+00	7.41e+00	6.97e+00	2.67e-02	2.12e-02	3.47e-02	2.55e-02	8.84e+00	8.74e+00	6.61e+00	8.29e+00	9.40e-02	8.76e-02	1.99e-02	6.44e-02
chrX	143802231	143827414	ENSMUSG00000067276	39.08	-	Capn6	protein_coding	1.16e-04	1.44e-02	-2.544321	3.27e+00	4.21e-03	1.00e+00	5.10e-04	3.32e+00	4.75e+00	5.00e+00	0.00e+00	2.30e-03	6.63e-03	7.91e-03	0.00e+00	0.00e+00	1.00e+00	3.00e+00	0.00e+00	0.00e+00	2.55e-04	1.79e-03	0.00e+00
chr16	85858170	85901125	ENSMUSG00000022894	40.04	-	Adamts5	protein_coding	1.26e-04	1.54e-02	1.326680	7.87e+00	4.24e-02	9.17e+00	1.07e-01	8.07e+00	8.18e+00	8.05e+00	7.18e+00	4.71e-02	5.09e-02	4.64e-02	2.53e-02	9.07e+00	9.66e+00	8.41e+00	9.54e+00	9.41e-02	1.42e-01	5.95e-02	1.31e-01
chr3	123076519	123236149	ENSMUSG00000050315	43.06	-	Synpo2	protein_coding	1.27e-04	1.54e-02	1.283346	7.12e+00	1.12e-02	8.31e+00	2.74e-02	7.42e+00	7.30e+00	7.35e+00	6.39e+00	1.33e-02	1.23e-02	1.27e-02	6.50e-03	8.96e+00	8.82e+00	7.19e+00	8.26e+00	3.89e-02	3.53e-02	1.14e-02	2.39e-02
chr15	98092589	98132447	ENSMUSG00000033065	48.49	+	Pfkm	protein_coding	1.28e-04	1.55e-02	-1.796467	5.60e+00	2.95e-02	3.39e+00	8.07e-03	5.21e+00	5.86e+00	5.43e+00	5.91e+00	2.19e-02	3.47e-02	2.56e-02	3.59e-02	1.58e+00	4.17e+00	4.81e+00	3.00e+00	1.22e-03	1.04e-02	1.64e-02	4.26e-03
chr5	134986214	134987472	ENSMUSG00000070473	62.75	+	Cldn3	protein_coding	1.36e-04	1.63e-02	-1.202346	6.41e+00	7.33e-02	5.19e+00	3.15e-02	5.67e+00	6.63e+00	7.68e+00	5.64e+00	3.66e-02	7.17e-02	1.49e-01	3.58e-02	4.91e+00	5.43e+00	6.44e+00	4.00e+00	2.12e-02	3.07e-02	6.29e-02	1.10e-02
chr15	101707070	101712891	ENSMUSG00000061527	52.15	-	Krt5	protein_coding	1.40e-04	1.66e-02	-1.376563	6.18e+00	6.79e-02	5.38e+00	2.58e-02	7.04e+00	6.73e+00	7.61e+00	3.32e+00	8.09e-02	6.48e-02	1.20e-01	5.56e-03	5.61e+00	4.91e+00	5.73e+00	5.29e+00	2.96e-02	1.79e-02	3.21e-02	2.35e-02
chr8	10984681	11008458	ENSMUSG00000038894	49.24	-	Irs2	protein_coding	1.44e-04	1.69e-02	1.579129	7.64e+00	5.74e-02	9.01e+00	1.72e-01	7.26e+00	7.70e+00	8.24e+00	7.35e+00	4.24e-02	5.78e-02	8.40e-02	4.52e-02	8.38e+00	9.13e+00	1.03e+01	8.22e+00	9.24e-02	1.56e-01	3.56e-01	8.29e-02
chr15	82370528	82380260	ENSMUSG00000061740	51.23	-	Cyp2d22	protein_coding	1.47e-04	1.71e-02	1.884728	6.07e+00	3.18e-02	7.27e+00	1.19e-01	5.21e+00	5.93e+00	6.91e+00	6.23e+00	1.58e-02	2.64e-02	5.24e-02	3.26e-02	6.04e+00	7.00e+00	9.65e+00	6.38e+00	2.86e-02	5.59e-02	3.54e-01	3.61e-02
chr12	113254830	113260236	ENSMUSG00000095079	51.30	-	Igha	IG_C_gene	1.48e-04	1.71e-02	-1.225069	1.04e+01	4.10e-01	8.91e+00	1.75e-01	1.04e+01	1.07e+01	1.15e+01	8.75e+00	3.41e-01	4.34e-01	7.56e-01	1.09e-01	1.03e+01	8.20e+00	1.01e+01	7.03e+00	3.09e-01	7.45e-02	2.84e-01	3.30e-02
chr7	89404355	89413134	ENSMUSG00000049791	45.91	+	Fzd4	protein_coding	1.54e-04	1.77e-02	1.315847	8.61e+00	6.49e-02	9.92e+00	1.62e-01	8.81e+00	8.52e+00	8.64e+00	8.46e+00	7.45e-02	6.06e-02	6.62e-02	5.84e-02	9.75e+00	1.03e+01	9.93e+00	9.73e+00	1.43e-01	2.02e-01	1.62e-01	1.41e-01
chr6	113697050	113711069	ENSMUSG00000056952	47.64	+	Tatdn2	protein_coding	1.56e-04	1.77e-02	-1.305394	9.28e+00	2.02e-01	7.97e+00	8.15e-02	9.26e+00	9.10e+00	9.10e+00	9.65e+00	1.97e-01	1.75e-01	1.76e-01	2.58e-01	7.77e+00	8.00e+00	8.38e+00	7.71e+00	6.97e-02	8.19e-02	1.07e-01	6.72e-02
chr6	30956023	30959078	ENSMUSG00000073209	54.35	-	Klf14	protein_coding	1.59e-04	1.80e-02	1.991588	3.10e+00	3.62e-03	5.20e+00	1.55e-02	4.32e+00	3.70e+00	2.81e+00	1.58e+00	7.05e-03	4.45e-03	2.23e-03	7.42e-04	5.67e+00	6.21e+00	4.00e+00	4.91e+00	1.85e-02	2.71e-02	5.56e-03	1.08e-02
chr8	88521354	88594884	ENSMUSG00000031661	51.89	+	Nkd1	protein_coding	1.63e-04	1.82e-02	1.581619	5.05e+00	8.78e-03	6.58e+00	2.68e-02	5.67e+00	5.25e+00	5.29e+00	4.00e+00	1.25e-02	9.28e-03	9.53e-03	3.76e-03	6.54e+00	7.64e+00	5.67e+00	6.46e+00	2.31e-02	4.97e-02	1.25e-02	2.18e-02
chr3	144796559	144819494	ENSMUSG00000028262	40.30	-	Clca3a2	protein_coding	1.74e-04	1.93e-02	-1.152266	6.69e+00	3.08e-02	5.87e+00	1.38e-02	7.33e+00	7.38e+00	8.06e+00	4.00e+00	3.26e-02	3.36e-02	5.40e-02	3.06e-03	6.21e+00	4.52e+00	6.88e+00	5.88e+00	1.49e-02	4.48e-03	2.38e-02	1.18e-02
chr5	115241412	115272898	ENSMUSG00000041740	47.78	-	Rnf10	protein_coding	1.75e-04	1.93e-02	-1.305168	8.65e+00	4.34e-02	7.33e+00	1.75e-02	8.64e+00	8.34e+00	8.77e+00	8.86e+00	4.26e-02	3.47e-02	4.66e-02	4.96e-02	7.21e+00	7.58e+00	7.64e+00	6.89e+00	1.57e-02	2.04e-02	2.12e-02	1.26e-02
chr4	126316047	126321703	ENSMUSG00000042558	54.91	-	Adprhl2	protein_coding	1.85e-04	2.03e-02	-1.510962	7.71e+00	7.01e-02	6.22e+00	2.44e-02	7.66e+00	7.64e+00	7.38e+00	8.16e+00	6.62e-02	6.56e-02	5.47e-02	9.39e-02	6.27e+00	6.46e+00	6.13e+00	6.02e+00	2.50e-02	2.87e-02	2.27e-02	2.11e-02
chr15	79053094	79062893	ENSMUSG00000033055	52.04	-	Ankrd54	protein_coding	1.96e-04	2.12e-02	-1.371899	8.24e+00	3.38e-02	6.86e+00	1.30e-02	8.52e+00	8.02e+00	8.15e+00	8.27e+00	4.08e-02	2.87e-02	3.15e-02	3.43e-02	6.95e+00	6.91e+00	7.10e+00	6.49e+00	1.37e-02	1.33e-02	1.51e-02	9.91e-03
chr6	123229843	123247021	ENSMUSG00000023349	38.44	+	Clec4n	protein_coding	1.97e-04	2.12e-02	-1.659688	7.39e+00	2.79e-02	5.74e+00	8.74e-03	7.07e+00	8.35e+00	6.79e+00	7.34e+00	2.04e-02	4.98e-02	1.69e-02	2.47e-02	6.55e+00	5.78e+00	4.86e+00	5.75e+00	1.43e-02	8.28e-03	4.29e-03	8.12e-03
chr13	118669791	118792115	ENSMUSG00000021732	37.11	+	Fgf10	protein_coding	1.97e-04	2.12e-02	1.208287	7.21e+00	2.82e-02	8.28e+00	6.53e-02	7.61e+00	7.21e+00	7.20e+00	6.81e+00	3.66e-02	2.77e-02	2.75e-02	2.09e-02	8.87e+00	8.83e+00	7.01e+00	8.41e+00	8.78e-02	8.54e-02	2.41e-02	6.41e-02
chr2	119797733	119818104	ENSMUSG00000027298	52.76	+	Tyro3	protein_coding	2.06e-04	2.19e-02	-1.066875	5.80e+00	9.58e-03	4.57e+00	4.50e-03	5.13e+00	6.43e+00	7.17e+00	4.46e+00	4.61e-03	1.15e-02	1.94e-02	2.84e-03	4.00e+00	4.09e+00	6.51e+00	3.70e+00	2.03e-03	2.17e-03	1.22e-02	1.63e-03
chr2	155701677	155729475	ENSMUSG00000038312	47.38	-	Edem2	protein_coding	2.07e-04	2.19e-02	-2.022368	5.53e+00	8.79e-03	3.43e+00	2.02e-03	5.09e+00	5.98e+00	5.00e+00	6.04e+00	6.07e-03	1.14e-02	5.70e-03	1.20e-02	3.46e+00	3.70e+00	4.25e+00	2.32e+00	1.84e-03	2.21e-03	3.31e-03	7.36e-04
chr9	26763044	26806468	ENSMUSG00000036395	44.25	-	Glb1l2	protein_coding	2.08e-04	2.19e-02	1.381656	1.04e+01	1.26e-01	1.15e+01	3.28e-01	1.05e+01	9.99e+00	1.06e+01	1.05e+01	1.31e-01	9.51e-02	1.46e-01	1.31e-01	1.18e+01	1.24e+01	1.00e+01	1.19e+01	3.25e-01	5.22e-01	9.65e-02	3.69e-01
chr5	105270702	105293698	ENSMUSG00000104713	40.34	-	Gbp6	protein_coding	2.13e-04	2.23e-02	1.359131	6.92e+00	9.99e-03	7.61e+00	2.57e-02	7.21e+00	6.70e+00	6.98e+00	6.81e+00	1.21e-02	8.47e-03	1.03e-02	9.12e-03	7.52e+00	7.67e+00	5.55e+00	9.69e+00	1.50e-02	1.66e-02	3.78e-03	6.76e-02
chr13	28948919	28953713	ENSMUSG00000076431	51.14	-	Sox4	protein_coding	2.19e-04	2.27e-02	-0.955454	8.12e+00	7.57e-02	6.81e+00	3.89e-02	7.85e+00	8.26e+00	8.65e+00	7.71e+00	6.06e-02	8.10e-02	1.06e-01	5.53e-02	6.69e+00	5.78e+00	8.47e+00	6.32e+00	2.70e-02	1.43e-02	9.34e-02	2.09e-02
chr9	8971791	8975773	ENSMUSG00000078117	40.05	+	Gm16485	protein_coding	2.23e-04	2.28e-02	1.342392	5.90e+00	1.45e-02	6.96e+00	3.70e-02	5.64e+00	5.61e+00	6.69e+00	5.64e+00	1.14e-02	1.12e-02	2.38e-02	1.14e-02	8.24e+00	7.44e+00	5.17e+00	6.98e+00	7.04e-02	4.03e-02	8.16e-03	2.91e-02
chr16	30064384	30067796	ENSMUSG00000022528	52.92	+	Hes1	protein_coding	2.23e-04	2.28e-02	-1.264624	8.27e+00	9.96e-02	7.02e+00	4.13e-02	8.23e+00	8.36e+00	8.73e+00	7.75e+00	9.43e-02	1.03e-01	1.33e-01	6.76e-02	7.34e+00	6.78e+00	7.27e+00	6.69e+00	5.06e-02	3.43e-02	4.81e-02	3.21e-02
chr7	19394437	19404104	ENSMUSG00000040714	56.10	-	Klc3	protein_coding	2.36e-04	2.38e-02	-1.200913	5.25e+00	1.81e-02	3.75e+00	7.65e-03	4.95e+00	5.83e+00	6.64e+00	3.58e+00	1.11e-02	2.06e-02	3.65e-02	4.06e-03	3.00e+00	2.00e+00	5.83e+00	4.17e+00	2.58e-03	1.11e-03	2.06e-02	6.27e-03
chr15	77015489	77050670	ENSMUSG00000018893	49.93	-	Mb	protein_coding	2.36e-04	2.38e-02	-1.439112	3.48e+00	2.03e-02	3.40e+00	7.10e-03	2.00e+00	5.32e+00	6.58e+00	0.00e+00	1.77e-03	2.31e-02	5.62e-02	0.00e+00	2.32e+00	2.58e+00	4.46e+00	4.25e+00	2.37e-03	2.96e-03	1.24e-02	1.06e-02
chr2	180597790	180622189	ENSMUSG00000027570	51.73	+	Col9a3	protein_coding	2.46e-04	2.43e-02	-1.567685	4.94e+00	8.70e-03	3.22e+00	2.79e-03	5.67e+00	5.58e+00	5.93e+00	2.58e+00	1.07e-02	1.01e-02	1.29e-02	1.07e-03	3.32e+00	1.58e+00	5.17e+00	2.81e+00	1.93e-03	4.30e-04	7.52e-03	1.29e-03
chr6	84571414	84593908	ENSMUSG00000063415	54.64	-	Cyp26b1	protein_coding	2.46e-04	2.43e-02	1.190310	7.56e+00	4.68e-02	8.74e+00	1.07e-01	7.73e+00	7.07e+00	7.52e+00	7.93e+00	5.14e-02	3.24e-02	4.43e-02	5.92e-02	8.88e+00	9.02e+00	8.13e+00	8.94e+00	1.15e-01	1.26e-01	6.82e-02	1.19e-01
chr6	34780432	34859459	ENSMUSG00000038836	38.76	+	Agbl3	protein_coding	2.47e-04	2.43e-02	1.318414	6.58e+00	4.38e-03	7.98e+00	1.10e-02	7.26e+00	6.89e+00	6.43e+00	5.73e+00	6.54e-03	5.07e-03	3.66e-03	2.24e-03	7.85e+00	8.39e+00	7.68e+00	7.99e+00	9.85e-03	1.44e-02	8.77e-03	1.09e-02
chr7	144929931	144939925	ENSMUSG00000070348	53.37	-	Ccnd1	protein_coding	2.50e-04	2.45e-02	-1.309673	9.80e+00	1.41e-01	8.49e+00	5.68e-02	9.94e+00	1.00e+01	9.94e+00	9.30e+00	1.52e-01	1.62e-01	1.52e-01	9.77e-02	8.75e+00	8.59e+00	8.03e+00	8.60e+00	6.68e-02	5.98e-02	4.04e-02	6.01e-02
chr8	71542922	71548085	ENSMUSG00000031813	54.82	+	Mvb12a	protein_coding	2.54e-04	2.47e-02	-1.584963	6.51e+00	1.22e-02	4.94e+00	3.99e-03	5.86e+00	6.79e+00	6.27e+00	7.14e+00	7.27e-03	1.40e-02	9.69e-03	1.79e-02	4.95e+00	4.39e+00	5.64e+00	4.75e+00	3.83e-03	2.55e-03	6.25e-03	3.32e-03
chr13	8885501	8892451	ENSMUSG00000058258	40.74	+	Idi1	protein_coding	2.62e-04	2.51e-02	1.340844	5.59e+00	1.09e-02	6.79e+00	2.81e-02	5.75e+00	5.49e+00	5.17e+00	5.95e+00	1.20e-02	9.98e-03	7.94e-03	1.38e-02	7.16e+00	7.01e+00	5.46e+00	7.52e+00	3.22e-02	2.90e-02	9.75e-03	4.13e-02
chr7	140890887	140892080	ENSMUSG00000083396	42.38	+	Gm15542	processed_pseudogene	2.63e-04	2.51e-02	-1.268022	9.30e+00	5.31e-01	8.07e+00	2.20e-01	9.56e+00	8.87e+00	9.95e+00	8.82e+00	6.02e-01	3.73e-01	7.89e-01	3.59e-01	8.53e+00	8.21e+00	7.59e+00	7.95e+00	2.94e-01	2.36e-01	1.53e-01	1.96e-01
chr10	80057416	80102698	ENSMUSG00000035673	55.43	-	Sbno2	protein_coding	2.63e-04	2.51e-02	-1.268236	7.34e+00	1.54e-01	6.08e+00	6.36e-02	6.64e+00	7.71e+00	6.44e+00	8.58e+00	7.89e-02	1.66e-01	6.86e-02	3.04e-01	5.21e+00	5.81e+00	7.43e+00	5.86e+00	2.87e-02	4.39e-02	1.36e-01	4.55e-02
chr7	5062143	5079938	ENSMUSG00000030435	48.02	+	U2af2	protein_coding	2.70e-04	2.57e-02	-1.330427	1.01e+01	8.22e-02	8.82e+00	3.26e-02	1.01e+01	1.05e+01	9.09e+00	1.05e+01	7.85e-02	1.06e-01	3.90e-02	1.05e-01	8.45e+00	8.85e+00	9.13e+00	8.83e+00	2.50e-02	3.31e-02	4.00e-02	3.25e-02
chr5	98854415	98884396	ENSMUSG00000029335	43.30	+	Bmp3	protein_coding	2.83e-04	2.66e-02	1.340544	5.82e+00	7.32e-03	7.14e+00	1.87e-02	6.15e+00	6.09e+00	5.64e+00	5.39e+00	9.03e-03	8.64e-03	6.32e-03	5.29e-03	7.52e+00	7.51e+00	6.61e+00	6.92e+00	2.36e-02	2.34e-02	1.25e-02	1.55e-02
chr9	59539540	59565109	ENSMUSG00000025232	47.06	+	Hexa	protein_coding	2.98e-04	2.79e-02	-1.400979	9.18e+00	4.19e-01	7.87e+00	1.58e-01	8.81e+00	9.58e+00	8.48e+00	9.83e+00	3.04e-01	5.18e-01	2.41e-01	6.15e-01	7.97e+00	7.99e+00	7.75e+00	7.78e+00	1.68e-01	1.72e-01	1.45e-01	1.48e-01
chr4	141444654	141467930	ENSMUSG00000006215	53.48	+	Zbtb17	protein_coding	3.17e-04	2.95e-02	-2.126532	4.88e+00	4.94e-03	2.60e+00	1.01e-03	4.46e+00	5.58e+00	4.00e+00	5.49e+00	3.27e-03	7.31e-03	2.33e-03	6.85e-03	2.58e+00	1.00e+00	3.81e+00	3.00e+00	7.78e-04	1.56e-04	2.02e-03	1.09e-03
chr15	102990607	102994111	ENSMUSG00000001657	50.16	+	Hoxc8	protein_coding	3.34e-04	3.08e-02	1.207569	9.14e+00	1.64e-01	1.02e+01	3.78e-01	8.89e+00	9.20e+00	9.00e+00	9.46e+00	1.36e-01	1.70e-01	1.47e-01	2.02e-01	9.94e+00	1.09e+01	9.34e+00	1.07e+01	2.83e-01	5.54e-01	1.87e-01	4.90e-01
chr9	106194947	106199746	ENSMUSG00000020253	55.54	-	Ppm1m	protein_coding	3.44e-04	3.14e-02	-1.470284	7.62e+00	2.05e-02	6.02e+00	7.34e-03	7.21e+00	7.69e+00	7.20e+00	8.38e+00	1.45e-02	2.04e-02	1.44e-02	3.27e-02	5.49e+00	6.92e+00	4.95e+00	6.70e+00	4.35e-03	1.19e-02	2.97e-03	1.02e-02
chr1	153283850	153287190	ENSMUSG00000103818	42.95	-	Gm38009	TEC	3.44e-04	3.14e-02	-2.678072	4.19e+00	1.83e-02	1.73e+00	2.19e-03	3.70e+00	3.46e+00	3.70e+00	5.88e+00	9.57e-03	7.97e-03	9.57e-03	4.63e-02	1.00e+00	1.00e+00	2.32e+00	2.58e+00	7.97e-04	7.97e-04	3.19e-03	3.99e-03

Download the DEG result list for Cond1_vs_Cond2.
Download the whole result list for Cond1_vs_Cond2.

References

Anders, S., and Huber, W. (2010). Differential expression analysis for sequence count data. Genome Biol 11, R106.
Planet, E., Attolini, C.S., Reina, O., Flores, O., and Rossell, D. (2012). htSeqTools: high-throughput sequencing quality control, processing and visualization in R. Bioinformatics 28, 589-590.
Tarazona, S., Garcia-Alcalde, F., Dopazo, J., Ferrer, A., and Conesa, A. (2011). Differential expression in RNA-seq: a matter of depth. Genome Res 21, 2213-2223.
Risso, D., Schwartz, K., Sherlock, G., and Dudoit, S. (2011). GC-content normalization for RNA-Seq data. BMC Bioinformatics 12, 480.
Benjamini, Y., and Hochberg, Y. (1995). Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing. Journal of the Royal Statistical Society Series B (Methodological) 57, 289-300.