Dear Sofia, please excuse if my terminology caused some misunderstanding. log transformed ratio of signal to input Dear Sofia, at http://genomics-lab.fleming.gr/fleming/DKlab/run392/run402/exonGencode.groups.rpkm.csv you can load the RPKM analysis per exon for the liver samples. The definition of the exon in col. 1 to 6: [1] "Geneid" [2] "Chr" [3] "Start" [4] "End" [5] "Strand" [6] "Length" The non-input RPKM values in col 7 to 18: [7] "DKR13r_M2RiPWt_1M" [8] "DKR14r_M2RiPWt_2M" [9] "DKR15r_M2RiPWt_3F" [10] "DKR16_M2RiPTg6105_1M" [11] "DKR17r_M2RiPTg6105_2M" [12] "DKR18_M2RiPTg6105_3F" [13] "DKR19_HuRRiPC57_1M" [14] "DKR21_HuRRiPC57_3F" [15] "DKR20_HURRIPC57_2M" [16] "DKR22_IgGRiPC57_1M" [17] "DKR23r_IgGRiPC57_2M" [18] "DKR24r_IgGRiPC57_3F" The input RPKM values (averaged over the 3 replicates) in col 19 to 21 [19] "iWT" [20] "iTg6105" [21] "iC57" The log2 foldchanges as defined below in (a) in col 22 to 30 [22] "M2RIP_WT1_fc" [23] "M2RIP_WT2_fc" [24] "M2RIP_WT3_fc" [25] "M2RIP_Tg6105_1_fc" [26] "M2RIP_Tg6105_2_fc" [27] "M2RIP_Tg6105_3_fc" [28] "HuR_RIPC57_1_fc" [29] "HuR_RIPC57_2_fc" [30] "HuR_RIPC57_3_fc" p-values and correced p-vaules (FDR or q-values) of a t.test for M2RIP_WTvsInputWT vs M2RIP_Tg6105vsInputTg610 [31] "M2RIP_WTvsInputWT_vs_M2RIP_Tg6105vsInputTg6105_pval" [32] "M2RIP_WTvsInputWT_vs_M2RIP_Tg6105vsInputTg6105_qval" The log2 foldchanges as defined below in (b) [33] "IgG_RIPC57_1_fc" [34] "IgG_RIPC57_2_fc" [35] "IgG_RIPC57_3_fc" p-values and correced p-vaules (FDR or q-values) of a t.test for HuR_RIPC57rVSinput_vs_IgG_RIPC57VSinput [36] "HuR_RIPC57r_vs_IgG_RIPC57_pval" [37] "HuR_RIPC57r_vs_IgG_RIPC57_qval" (a) # M2RIP_WT vs InputWT r$M2RIP_WT1_fc=log2((1+r$DKR13r_M2RiPWt_1M)/(1+r$iWT)); r$M2RIP_WT2_fc=log2((1+r$DKR14r_M2RiPWt_2M)/(1+r$iWT)); r$M2RIP_WT3_fc=log2((1+r$DKR15r_M2RiPWt_3F)/(1+r$iWT)); # M2RIP_Tg6105 vs InputTg6105 r$M2RIP_Tg6105_1_fc=log2((1+r$DKR16_M2RiPTg6105_1M )/(1+r$iTg6105)); r$M2RIP_Tg6105_2_fc=log2((1+r$DKR17r_M2RiPTg6105_2M)/(1+r$iTg6105)); r$M2RIP_Tg6105_3_fc=log2((1+r$DKR18_M2RiPTg6105_3F )/(1+r$iTg6105)); # HuR_RIPC57 vs InputC57 r$HuR_RIPC57_1_fc=log2((1+r$DKR19_HuRRiPC57_1M)/(1+r$iC57)); r$HuR_RIPC57_2_fc=log2((1+r$DKR21_HuRRiPC57_3F)/(1+r$iC57)); r$HuR_RIPC57_3_fc=log2((1+r$DKR20_HURRIPC57_2M)/(1+r$iC57)); (b) r$IgG_RIPC57_1_fc=log2((1+r$DKR22_IgGRiPC57_1M)/(1+r$iC57)); r$IgG_RIPC57_2_fc=log2((1+r$DKR23r_IgGRiPC57_2M)/(1+r$iC57)); r$IgG_RIPC57_3_fc=log2((1+r$DKR24r_IgGRiPC57_3F)/(1+r$iC57)); I'd suggest to sort either for [32] "M2RIP_WTvsInputWT_vs_M2RIP_Tg6105vsInputTg6105_qval" or [37] "HuR_RIPC57r_vs_IgG_RIPC57_qval" and inspect the cases with a qval<=0.05. BW, Martin h=which(na.omit(r$HuR_RIPC57r_vs_IgG_RIPC57_qval)<=0.1) > s=r[h,] > s[,1] [1] Actr1b Gpr45 Sf3b1 Atg9a Gin1 [6] Snrpe Nr5a2 Marc2 Man1b1 Edf1 [11] Mamdc4 Abl1 Abl1 Gm37159 Wipf1 [16] Bloc1s6 Fbn1 Trpm7 Ncaph Xrn2 [21] Ppp4r1l-ps Ccdc22 Gria3 Gria3 Maged1 [26] 5830417I10Rik Pi4kb Psmd4 Bcl9 Gstm1 [31] Amigo1 Gm6135 Gm26691 Rnf19b Clic4 [36] Pla2g2c Kmt2e Abcb8 Ugdh Pigg [41] 1700069L16Rik Rpl6 Rpl6 Nsun5 Fry [46] Ppp1r9a Phf14 Phf14 Chchd6 C1s1 [51] Zfp526 Gramd1a Aamdc Sox6 Itgax [56] Wdr11 Zbtb24 Gm15343 Socs2 Erbb3 [61] Gm31135 A630009H07Rik Tti2 Uba52 Uba52 [66] Lonp2 Lonp2 Vac14 Vdac2 Vdac2 [71] 1700108J01Rik Msantd2 Olfr891