Dear Sofia,

please see the report for your 8 QuantSeq samples at:
http://genomics-lab.fleming.gr/fleming/ITlab/run297sofia/cuffdiff_wt_vs_SET9ko/cufflinks_report.html

From there, you can browse UCSC tracks,
get the tables with gene and isoform expression
and inspect several plots (Panagioti, if you don't
mind I took a bit of explanatory text from metaseqR
to explain the plots).

Let us know if you need anything else.

Best wishes,
Martin





Dear Pantelis

here are the next results, starting with Sofia.
To proceed (and as they ask me about progess), I'd send this to Sofia too.
BW,
Martin

1)
tracks normalized to the smallest library
IT3R15-SET9ko5 with 4335051 reads are at:

http://genomics-lab.fleming.gr/cgi-bin/hgTracks?db=mm10&hubUrl=http://genomics-lab.fleming.gr/fleming/ITlab/run297sofia/hub.txt

2)
Differentially expressed genes for the contrast wt_vs_SET9ko are at:
http://genomics-lab.fleming.gr/fleming/ITlab/run297sofia/cuffdiff_wt_vs_SET9ko/gene_exp.diff.xlsx

3)
Differentially expressed isoforms with biotype information for the contrast wt_vs_SET9ko are at:
http://genomics-lab.fleming.gr/fleming/ITlab/run297sofia/cuffdiff_wt_vs_SET9ko/isoform_exp.diff.xlsx

4)
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.

MDS plot using gene expression is at:
http://genomics-lab.fleming.gr/fleming/ITlab/run297sofia/cuffdiff_wt_vs_SET9ko/wt_vs_SET9ko_genes_MDSplot.png
MDS plot using isoform expression is at:
http://genomics-lab.fleming.gr/fleming/ITlab/run297sofia/cuffdiff_wt_vs_SET9ko/wt_vs_SET9ko_isoforms_MDSplot.png

5)
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 with q-value cutoff = 0.05 is at:
http://genomics-lab.fleming.gr/fleming/ITlab/run297sofia/cuffdiff_wt_vs_SET9ko/wt_vs_SET9ko_known_genes_alpha0.05_with_replicates.png

6)
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.

A volcano plot for all genes is at:
http://genomics-lab.fleming.gr/fleming/ITlab/run297sofia/cuffdiff_wt_vs_SET9ko/wt_vs_SET9ko_genes_alpha0.05_volcano.png







http://genomics-lab.fleming.gr/fleming/ITlab/run297sofia/hub.txt