library(MASS) library(RColorBrewer) rf <- colorRampPalette(rev(brewer.pal(11,'Spectral'))) r <- rf(32) png("dens_m0_ko_rna_vs_poly_pcg.png",width=1024,height=1024,pointsize = 22) a=all_m0[(!is.na(all_m0[,32])&!is.na(all_m0[,16])),] k2 <- kde2d(log2(1+(a[,32])),log2(1+(a[,16])),n=500,lims=c(0,9,0,9)) #k2=k #k2$z=log10(k$z+1e-3) image(k2, col=r,xlab="log2(RPKM_abundance)",ylab="log2(RPKM_translation)") #contour(k2, add = TRUE,labcex=1) # from base graphics package contour(k2, add = TRUE,vfont = c("sans serif", "plain"),labcex=0.65) dev.off() png("dens_m0_wt_rna_vs_poly_pcg.png",width=1024,height=1024,pointsize = 22) a=all_m0[(!is.na(all_m0[,33])&!is.na(all_m0[,17])),] k2 <- kde2d(log2(1+(a[,33])),log2(1+(a[,17])),n=500,lims=c(0,9,0,9)) #k2=k #k2$z=log10(k$z+1e-3) image(k2, col=r,xlab="log2(RPKM_abundance)",ylab="log2(RPKM_translation)") #contour(k2, add = TRUE,labcex=1) contour(k2, add = TRUE,vfont = c("sans serif", "plain"),labcex=0.65) dev.off() png("dens_m2_ko_rna_vs_poly_pcg.png",width=1024,height=1024,pointsize = 22) a=all_m2[(!is.na(all_m2[,32])&!is.na(all_m2[,16])),] k2 <- kde2d(log2(1+(a[,32])),log2(1+(a[,16])),n=500,lims=c(0,9,0,9)) #k2=k #k2$z=log10(k$z+1e-3) image(k2, col=r,xlab="log2(RPKM_abundance)",ylab="log2(RPKM_translation)") #contour(k2, add = TRUE,labcex=1) contour(k2, add = TRUE,vfont = c("sans serif", "plain"),labcex=0.65) dev.off() png("dens_m2_wt_rna_vs_poly_pcg.png",width=1024,height=1024,pointsize = 22) a=all_m2[(!is.na(all_m2[,33])&!is.na(all_m2[,17])),] k2 <- kde2d(log2(1+(a[,33])),log2(1+(a[,17])),n=500,lims=c(0,9,0,9)) #k2=k #k2$z=log10(k$z+1e-3) image(k2, col=r,xlab="log2(RPKM_abundance)",ylab="log2(RPKM_translation)") #contour(k2, add = TRUE,labcex=1) contour(k2, add = TRUE,vfont = c("sans serif", "plain"),labcex=0.65) dev.off() #@ diff of log2RPKM png("dens_m0_diff_ko_minus_wt_rna_vs_poly_pcg.png",width=2001,height=2001,pointsize = 44) a=all_m0[(!is.na(all_m0[,32])&!is.na(all_m0[,16]))&(!is.na(all_m0[,33])&!is.na(all_m0[,17])),] k <- kde2d(log2(1+(a[,32]))-log2(1+(a[,33])),log2(1+(a[,16]))-log2(1+(a[,17])),n=400,lims=c(-7.4,5.5,-6.1,7.5)) k2=k k2$z=log10(k$z+1e-12) image(k2, col=r,xlab="log2 foldchange abundance",ylab="log2 foldchange translation") grid() contour(k2, add = TRUE,vfont = c("sans serif", "plain"),labcex=0.65,nlevels=8) # from base graphics package dev.off() png("dens_m1_diff_ko_minus_wt_rna_vs_poly_pcg.png",width=2001,height=2001,pointsize = 44) a=all_m1[(!is.na(all_m1[,32])&!is.na(all_m1[,16]))&(!is.na(all_m1[,33])&!is.na(all_m1[,17])),] k <- kde2d(log2(1+(a[,32]))-log2(1+(a[,33])),log2(1+(a[,16]))-log2(1+(a[,17])),n=400,lims=c(-7.4,5.5,-6.1,7.5)) k2=k k2$z=log10(k$z+1e-12) image(k2, col=r,xlab="log2 foldchange abundance",ylab="log2 foldchange translation") grid() contour(k2, add = TRUE,vfont = c("sans serif", "plain"),labcex=0.65,nlevels=8) # from base graphics package dev.off() png("dens_m2_diff_ko_minus_wt_rna_vs_poly_pcg.png",width=2001,height=2001,pointsize = 44) a=all_m2[(!is.na(all_m2[,32])&!is.na(all_m2[,16]))&(!is.na(all_m2[,33])&!is.na(all_m2[,17])),] k <- kde2d(log2(1+(a[,32]))-log2(1+(a[,33])),log2(1+(a[,16]))-log2(1+(a[,17])),n=400,lims=c(-7.4,5.5,-6.1,7.5)) k2=k k2$z=log10(k$z+1e-12) image(k2, col=r,xlab="log2 foldchange abundance",ylab="log2 foldchange translation") grid() contour(k2, add = TRUE,vfont = c("sans serif", "plain"),labcex=0.65,nlevels=8) # from base graphics package dev.off() png("dens_2h_diff_ko_minus_wt_rna_vs_poly_pcg.png",width=2001,height=2001,pointsize = 44) a=all_2h[(!is.na(all_2h[,32])&!is.na(all_2h[,16]))&(!is.na(all_2h[,33])&!is.na(all_2h[,17])),] k <- kde2d(log2(1+(a[,32]))-log2(1+(a[,33])),log2(1+(a[,16]))-log2(1+(a[,17])),n=400,lims=c(-7.4,5.5,-6.1,7.5)) k2=k k2$z=log10(k$z+1e-12) image(k2, col=r,xlab="log2 foldchange abundance",ylab="log2 foldchange translation") grid() contour(k2, add = TRUE,vfont = c("sans serif", "plain"),labcex=0.65,nlevels=8) # from base graphics package dev.off() png("dens_6h_diff_ko_minus_wt_rna_vs_poly_pcg.png",width=2001,height=2001,pointsize = 44) a=all_6h[(!is.na(all_6h[,32])&!is.na(all_6h[,16]))&(!is.na(all_6h[,33])&!is.na(all_6h[,17])),] k <- kde2d(log2(1+(a[,32]))-log2(1+(a[,33])),log2(1+(a[,16]))-log2(1+(a[,17])),n=400,lims=c(-7.4,5.5,-6.1,7.5)) k2=k k2$z=log10(k$z+1e-12) image(k2, col=r,xlab="log2 foldchange abundance",ylab="log2 foldchange translation") grid() contour(k2, add = TRUE,vfont = c("sans serif", "plain"),labcex=0.65,nlevels=8) # from base graphics package dev.off() # test tested genes a=all_m2[all_m2$geneID.x=="Dab2",] print(c(log2(1+(a[,32]))-log2(1+(a[,33])),log2(1+(a[,16]))-log2(1+(a[,17])))) m2: EnsemblID logFC.x logCPM.x PValue.x FDR.x geneID.x genelength.x CPM_KO_m2_replicate_I.x CPM_KO_m2_replicate_II.x CPM_WT_m2_replicate_I.x CPM_WT_m2_replicate_II.x RPKM_KO_m2_replicate_I.x RPKM_KO_m2_replicate_II.x RPKM_WT_m2_replicate_I.x RPKM_WT_m2_replicate_II.x RPKM_KO_m2.x RPKM_WT_m2.x logFC.y logCPM.y PValue.y FDR.y geneID.y genelength.y CPM_KO_m2_replicate_I.y CPM_KO_m2_replicate_II.y CPM_WT_m2_replicate_I.y CPM_WT_m2_replicate_II.y RPKM_KO_m2_replicate_I.y RPKM_KO_m2_replicate_II.y RPKM_WT_m2_replicate_I.y RPKM_WT_m2_replicate_II.y RPKM_KO_m2.y RPKM_WT_m2.y ENSMUSG00000022150 0.132107113100571 10.2892120441771 0.331913609425355 1 Dab2 2776.27 1221.56603540568 1395.42241055113 1221.66278736551 1166.31910126626 440.002606160669 502.624892590104 440.037455782582 420.102908314486 471.313749375386 430.070182048534 -1.18653374049147 9.28065118430811 0.00230156674087398 0.0943898662949966 Dab2 2776.27 426.972318667644 326.359251217271 961.026080556944 755.079232071391 153.793513839664 117.553138281677 346.157283173807 271.976152201115 135.67332606067 309.066717687461 ENSMUSG00000033335 -0.0899381293206148 7.71702709380325 0.475478796826375 1 Dnm2 3457.67 208.128905491291 199.505628534437 224.044798713337 209.784286884035 60.1933977190684 57.6994416860017 64.7964666128743 60.6721540470997 58.9464197025351 62.734310329987 -1.84820693331423 5.48337709162363 0.00020140449743313 0.0182692729839096 Dnm2 3457.67 15.3097644143777 20.2567811100375 66.7182064788425 60.3169800767087 4.42776910878646 5.85850619348795 19.2957125691123 17.4444004421211 5.1431376511372 18.3700565056167 m0: ENSMUSG00000022150 0.384608924394437 8.4667260849825 0.298172975084381 1 Dab2 2776.27 583.223964840449 218.01762162491 255.594292367758 358.125933418394 210.074655865766 78.5289693095087 92.0639175468372 128.995354709158 144.301812587637 110.529636127998 0.516268242555404 7.12196903296183 0.246829592763874 0.775845449687528 Dab2 2776.27 130.920280694042 185.84433363292 107.18913732916 114.792892264839 47.1568978139886 66.9402953001401 38.6090464288991 41.347884847237 57.0485965570644 39.9784656380681 ENSMUSG00000033335 -0.0822073356400329 8.0492193257839 0.707547885501214 1 Dnm2 3457.67 243.646277248694 270.935855038506 270.288103436926 274.478280237585 70.4654513729459 78.3579274593892 78.1705898587563 79.3824396884564 74.4116894161675 78.7765147736063 -0.857910094142138 6.10757625834405 0.0599751124251922 0.442863846034911 Dnm2 3457.67 44.1855947342392 50.0350129011708 83.369329033791 88.3022248191066 12.7790086197466 14.4707311285261 24.1114186818843 25.5380718284587 13.6248698741363 24.8247452551715 Dab2 logFC_rna =0.132107113100571 log2(136.67332606067)-log2( 310.066717687461) log2FC_poly= -1.181847 log2FC_rna_m0=0.384608924394437, log2FC_poly_m0=0.516268242555404 log2FC_rna_m2=0.132107113100571, log2FC_poly_m2=-1.181847 Dnm2 logFC_rna = -0.0899381293206148 log2FC_poly= -1.84820693331423 log2FC_rna_m2=-0.0899381293206148, log2FC_poly_m2=-1.84820693331423 -0.0822073356400329 -0.857910094142138 #@ t-tests plot (log2(1+(a[,32]))-log2(1+(a[,33])),log2(1+(a[,16]))-log2(1+(a[,17])),pch=".") > th=2 lpWT_m2=all_m2[ abs(all_m2$logFC.y) mean of x 2.000000e+00 3.039763e-06 -1.609448e-02 > > lpWT_m2=all_m0[ abs(all_m0$logFC.y) mean of x 2.000000e+00 2.794738e-86 -1.127235e-01 > > lpWT_m2=all_m1[ abs(all_m1$logFC.y) mean of x 2.000000e+00 1.660528e-24 -3.424133e-02 > > lpWT_m2=all_2h[ abs(all_2h$logFC.y) mean of x 2.000000e+00 3.335461e-36 6.336078e-02 > > lpWT_m2=all_6h[ abs(all_6h$logFC.y) mean of x 2.000000e+00 1.044731e-53 -6.415852e-02