Dear Dimitris, at http://genomics-lab.fleming.gr/cgi-bin/hgTracks?db=mm10&hubUrl=http://genomics-lab.fleming.gr/fleming/DKlab/run347/hub.txt you will find tracks for the 2 QuantSeq runs merged, normalized to the smallest library (mergedDK3R6-K3) containing 2884541 reads sample(s) n_reads mergedDK3R10b-K23L4 4261384 mergedDK3R11-K2L4 4498530 mergedDK3R12-K3L4 5883918 mergedDK3R1r-C1 3904712 mergedDK3R2r-C2 3808001 mergedDK3R3r-C3 4919353 mergedDK3R4b-K23 3391024 mergedDK3R5-K2 4062319 mergedDK3R6-K3 2884541 mergedDK3R7-C1L4 3835289 mergedDK3R8-C2L4 4237759 mergedDK3R9r-C3L4 3804990 BW, Martin At http://genomics-lab.fleming.gr/fleming/DKlab/run343/metaseqr_quantseq_run347merged343_wo_C3L4_C3-K23-K23L4/index.html is the requested configuration. BW Martin #@ Ok Martin-I have gone thoroughly through all the sets. Based on my observations i need you to do one last thing-prepare a metaseeker report (merged 347, 343) but omit C3, C3L4, K23 & K23L4. I am excluding these because the C3's have quite divergent values and the K23's seem to have AUF1 leftovers whereas it shouldn't. Best, Dimitris #@ Dear Dimitris, the new run (run347) had the following library sizes: sample n_reads DK3R1r-C1 1944729 DK3R2r-C2 1807809 DK3R3r-C3 2551996 DK3R4b-K23 1435615 DK3R5-K2 1953628 DK3R6-K3 1341731 DK3R7-C1L4 1336227 DK3R8-C2L4 1981573 DK3R9r-C3L4 1862842 DK3R10b-K23L4 2079861 DK3R11-K2L4 2353699 DK3R12-K3L4 3025313 Run437 was analyzed anlone at: http://genomics-lab.fleming.gr/fleming/DKlab/run347/metaseqr_quantseq_run347/index.html The analysis with the libraries from run344 and run347 merged is at: http://genomics-lab.fleming.gr/fleming/DKlab/run347/metaseqr_quantseq_run347merged343/index.html The analysis with the libraries from run344 and run347 merged using the gene set with more than 2 "ATTTA" motifs is at: http://genomics-lab.fleming.gr/fleming/DKlab/run347/metaseqr_quantseq_run347merged343GE3AREsite-geneset/index.html BW, Martin Dear Dimitris, attached are those genes that have more than 2 "ATTTA" motifs and the location of those motifs. Using these genes, the results are at http://genomics-lab.fleming.gr/fleming/DKlab/run343/metaseqr_quantseq_run343c/index.html BW, Martin #@ 28042017 Yes, please use the latest edition and use the "ATTTA" motif at first-we seek those that have more than 2 of those. #@ Dear Dimitris, at http://genomics-lab.fleming.gr/fleming/DKlab/run343/metaseqr_quantseq_run343b/index.html are the comparisons as you defined them (note again the used naming convention: in A_vs_B, A is always the reference). Concerning the AU-rich elements, should we use the latest edition at http://rna.tbi.univie.ac.at/AREsite2/welcome and shall we include all motifs? BW, Martin #@ Dimitris Kontoyiannis 11:31 AM (1 hour ago) to me, Dimitris, Pantelis, Harokopos Hi Martin, Thanks for the update.The comparisons that i am interested in are: C vs K which should be derived from C=C1,C2 and K=K23, K2,K3, CL4 vs KL4 which should be derived from CL4=C1L4, C2L4 and KL4=K23L4,K2L4,K3L4 C vs CL4 & K vs KL4 Now given the low count of reads and since the samples are to be run again, i am excluding C3 and C3L4 since they appear as outliers in the MDS plots. After the final analysis, i would require an extra filtering if possible-to remove genes with less than 2 AU-rich elements. People are doing this by taking datasets from the ARESite database. Best, Dimitris #@ Dear Dimitris, the processing of the 3UTRseq samples in run343 has finished. At http://genomics-lab.fleming.gr/cgi-bin/hgTracks?db=mm10&hubUrl=http://genomics-lab.fleming.gr/fleming/DKlab/run343/hub.txt you will find tracks, normalized to the smallest library, DK3R6-K3 with 1586921 reads. The library sizes are as follows: sample n_reads DK3R1r-C1 2031406 DK3R2r-C2 2073352 DK3R3r-C3 2474771 DK3R4b-K23 2049128 DK3R5-K2 2181338 DK3R6-K3 1586921 DK3R7-C1L4 2564939 DK3R8-C2L4 2316573 DK3R9r-C3L4 1994621 DK3R10b-K23L4 2251092 DK3R11-K2L4 2209027 DK3R12-K3L4 2980532 At http://genomics-lab.fleming.gr/fleming/DKlab/run343/metaseqr_quantseq_run343/index.html you will find the metaseqR [1] differential gene expression analysis using the contrasts "C_vs_K","C_vs_C_L4","C_vs_K_L4","K_vs_C_L4","K_vs_K_L4","C_L4_vs_K_L4" (note the used naming convention: in A_vs_B, A is always the reference). Let me know if you need other contrasts. Best wishes, Martin [1] Moulos P and Hatzis P “Systematic integration of RNA-Seq statistical algorithms for accurate detection of differential gene expression patterns.” Nucl. Acids Res. (2014) doi: 10.1093/nar/gku1273 http://nar.oxfordjournals.org/content/early/2014/12/01/nar.gku1273.abstract.