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Commit 2b3f120a authored by Venkat Malladi's avatar Venkat Malladi
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Finish the AC-16 analysis.

parent 346ab5df
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RIP-seq.Rmd
View file @ 2b3f120a
......@@ -1059,3 +1059,300 @@ alk_allsnotx_rna_rpkm$gene_name <- as.character(gencode_sn_mapping[sn_inx,"V3"])
write.table(alk_allsnotx_rna_rpkm, file="ac16-snRNA_RPKM_RNA.tsv", quote=F, sep="\t", row.names=F, col.names=T)
```
```{r alignments TNF}
ALKT_RNA1 <- "/Volumes/project/GCRB/Lee_Lab/s163035/DK_RIP-seq/PARP1_RNAseq_in_AC16_MCF7_withTNFa_E2/raw/Sample_ALKT_RNA1/align-star-se.sh-1.0.0/ALKT_RNA1_GCCAAT_L007_R1.rDNA.filtered.fastq.gz_filtered_chrMAligned.sortedByCoord.out.bam"
ALKT_RNA2 <- "/Volumes/project/GCRB/Lee_Lab/s163035/DK_RIP-seq/PARP1_RNAseq_in_AC16_MCF7_withTNFa_E2/raw/Sample_ALKT_RNA2/align-star-se.sh-1.0.0/ALKT_RNA2_TAGCTT_L007_R1.rDNA.filtered.fastq.gz_filtered_chrMAligned.sortedByCoord.out.bam"
ALKT_RIP_PI1 <- "/Volumes/project/GCRB/Lee_Lab/s163035/DK_RIP-seq/PARP1_RIPseq_in_AC16_MCF7_withTNFa_E2/raw/Sample_ALKT_RIP1_PI/align-star-se.sh-2.0.0/ALKT_RIP1_PI_ATGTCA_L003_R1.rDNA.filtered.fastq.gz_filtered_chrMAligned.sortedByCoord.out.bam"
ALKT_RIP_PI2 <- "/Volumes/project/GCRB/Lee_Lab/s163035/DK_RIP-seq/PARP1_RIPseq_in_AC16_MCF7_withTNFa_E2/raw/Sample_ALKT_RIP2_PI/align-star-se.sh-2.0.0/ALKT_RIP2_PI_GAGTGG_L003_R1.rDNA.filtered.fastq.gz_filtered_chrMAligned.sortedByCoord.out.bam"
ALKT_RIP_PARP1 <- "/Volumes/project/GCRB/Lee_Lab/s163035/DK_RIP-seq/PARP1_RIPseq_in_AC16_MCF7_withTNFa_E2/raw/Sample_ALKT_RIP1_PARP1/align-star-se.sh-2.0.0/ALKT_RIP1_PARP1_CCGTCC_L006_R1.rDNA.filtered.fastq.gz_filtered_chrMAligned.sortedByCoord.out.bam"
ALKT_RIP_PARP2 <- "/Volumes/project/GCRB/Lee_Lab/s163035/DK_RIP-seq/PARP1_RIPseq_in_AC16_MCF7_withTNFa_E2/raw/Sample_ALKT_RIP2_PARP1/align-star-se.sh-2.0.0/ALKT_RIP2_PARP1_GGTAGC_L006_R1.rDNA.filtered.fastq.gz_filtered_chrMAligned.sortedByCoord.out.bam"
```
```{r counts TNF}
ALKT_RNA1_counts_ref <- CountRefseq(ref_tx, ALKT_RNA1, all_sn_tx, removeSNORNA=TRUE)
ALKT_RNA2_counts_ref <- CountRefseq(ref_tx, ALKT_RNA2, all_sn_tx, removeSNORNA=TRUE)
ALKT_RNA1_counts_lnc <- CountRefseq(lnc_tx, ALKT_RNA1, all_sn_tx, removeSNORNA=TRUE)
ALKT_RNA2_counts_lnc <- CountRefseq(lnc_tx, ALKT_RNA2, all_sn_tx, removeSNORNA=TRUE)
ALKT_RNA1_counts_sn <- CountSNRNA(sn_tx, ALKT_RNA1)
ALKT_RNA2_counts_sn <- CountSNRNA(sn_tx, ALKT_RNA2)
ALKT_RNA1_counts_sno <- CountSNRNA(sno_tx, ALKT_RNA1)
ALKT_RNA2_counts_sno <- CountSNRNA(sno_tx, ALKT_RNA2)
ALKT_RIP_PI1_counts_ref <- CountRefseq(ref_tx, ALKT_RIP_PI1, all_sn_tx, removeSNORNA=TRUE)
ALKT_RIP_PI2_counts_ref <- CountRefseq(ref_tx, ALKT_RIP_PI2, all_sn_tx, removeSNORNA=TRUE)
ALKT_RIP_PI1_counts_lnc <- CountRefseq(lnc_tx, ALKT_RIP_PI1, all_sn_tx, removeSNORNA=TRUE)
ALKT_RIP_PI2_counts_lnc <- CountRefseq(lnc_tx, ALKT_RIP_PI2, all_sn_tx, removeSNORNA=TRUE)
ALKT_RIP_PI1_counts_sn <- CountSNRNA(sn_tx, ALKT_RIP_PI1)
ALKT_RIP_PI2_counts_sn <- CountSNRNA(sn_tx, ALKT_RIP_PI2)
ALKT_RIP_PI1_counts_sno <- CountSNRNA(sno_tx, ALKT_RIP_PI1)
ALKT_RIP_PI2_counts_sno <- CountSNRNA(sno_tx, ALKT_RIP_PI2)
ALKT_RIP_PARP1_counts_ref <- CountRefseq(ref_tx, ALKT_RIP_PARP1, all_sn_tx, removeSNORNA=TRUE)
ALKT_RIP_PARP2_counts_ref <- CountRefseq(ref_tx, ALKT_RIP_PARP2, all_sn_tx, removeSNORNA=TRUE)
ALKT_RIP_PARP1_counts_lnc <- CountRefseq(lnc_tx, ALKT_RIP_PARP1, all_sn_tx, removeSNORNA=TRUE)
ALKT_RIP_PARP2_counts_lnc <- CountRefseq(lnc_tx, ALKT_RIP_PARP2, all_sn_tx, removeSNORNA=TRUE)
ALKT_RIP_PARP1_counts_sn <- CountSNRNA(sn_tx, ALKT_RIP_PARP1)
ALKT_RIP_PARP2_counts_sn <- CountSNRNA(sn_tx, ALKT_RIP_PARP2)
ALKT_RIP_PARP1_counts_sno <- CountSNRNA(sno_tx, ALKT_RIP_PARP1)
ALKT_RIP_PARP2_counts_sno <- CountSNRNA(sno_tx, ALKT_RIP_PARP2)
```
# RPKM Cutoff
``` {r rpkm TNF}
ALKT_RNA_counts_ref <- ALKT_RNA1_counts_ref$counts + ALKT_RNA2_counts_ref$counts
ALKT_RNA_lib_ref <- ALKT_RNA1_counts_ref$lib + ALKT_RNA2_counts_ref$lib
ALKT_RNA_ref_d <- DGEList(counts=as.matrix(ALKT_RNA_counts_ref), lib.size=ALKT_RNA_lib_ref)
ALKT_RNA_ref_rpkm <- data.frame(rpkm(ALKT_RNA_ref_d,width(ref_tx)))
alkt_pc_rpkm <- ref_tx[ALKT_RNA_ref_rpkm>=1]
NROW(unique(unlist(mcols(alkt_pc_rpkm)$tx_name)))
NROW(unique(unlist(mcols(alkt_pc_rpkm)$gene_name)))
ALKT_RIP_PARP_counts_ref <- ALKT_RIP_PARP1_counts_ref$counts + ALKT_RIP_PARP2_counts_ref$counts
ALKT_RIP_PARP_lib_ref <- ALKT_RIP_PARP1_counts_ref$lib + ALKT_RIP_PARP2_counts_ref$lib
ALKT_RIP_PI_counts_ref <- ALKT_RIP_PI1_counts_ref$counts + ALKT_RIP_PI2_counts_ref$counts
ALKT_RIP_PI_lib_ref <- ALKT_RIP_PI1_counts_ref$lib + ALKT_RIP_PI1_counts_ref$lib
ALKT_RIP_PI_d <- DGEList(counts=as.matrix(ALKT_RIP_PI_counts_ref), lib.size=ALKT_RIP_PI_lib_ref)
ALKT_RIP_PI_rpkm <- data.frame(rpkm(ALKT_RIP_PI_d,width(ref_tx)))
ALKT_RIP_PARP_d <- DGEList(counts=as.matrix(ALKT_RIP_PARP_counts_ref), lib.size=ALKT_RIP_PARP_lib_ref)
ALKT_RIP_PARP_rpkm <- data.frame(rpkm(ALKT_RIP_PARP_d,width(ref_tx)))
ALKT_RIP_FC <- data.frame((ALKT_RIP_PARP_rpkm+1)/(ALKT_RIP_PI_rpkm+1))
alkt_pc_rpkm_fc <- ref_tx[ALKT_RNA_ref_rpkm>=1 & ALKT_RIP_FC>=2 ]
NROW(unique(unlist(mcols(alkt_pc_rpkm_fc)$tx_name)))
NROW(unique(unlist(mcols(alkt_pc_rpkm_fc)$gene_name)))
pc_ratio <- NROW(unique(unlist(mcols(alkt_pc_rpkm_fc)$gene_name)))/NROW(unique(unlist(mcols(alkt_pc_rpkm)$gene_name)))
ALKT_RNA_counts_lnc <- ALKT_RNA1_counts_lnc$counts + ALKT_RNA2_counts_lnc$counts
ALKT_RNA_lib_lnc <- ALKT_RNA1_counts_lnc$lib + ALKT_RNA2_counts_lnc$lib
ALKT_RNA_lnc_d <- DGEList(counts=as.matrix(ALKT_RNA_counts_lnc), lib.size=ALKT_RNA_lib_lnc)
ALKT_RNA_lnc_rpkm <- data.frame(rpkm(ALKT_RNA_lnc_d,width(lnc_tx)))
alkt_lnc_rpkm <- lnc_tx[ALKT_RNA_lnc_rpkm>=1]
NROW(unique(unlist(mcols(alkt_lnc_rpkm)$tx_name)))
NROW(unique(unlist(mcols(alkt_lnc_rpkm)$gene_id)))
ALKT_RIP_PARP_counts_lnc <- ALKT_RIP_PARP1_counts_lnc$counts + ALKT_RIP_PARP2_counts_lnc$counts
ALKT_RIP_PARP_lib_lnc<- ALKT_RIP_PARP1_counts_lnc$lib + ALKT_RIP_PARP2_counts_lnc$lib
ALKT_RIP_PI_counts_lnc <- ALKT_RIP_PI1_counts_lnc$counts + ALKT_RIP_PI2_counts_lnc$counts
ALKT_RIP_PI_lib_lnc <- ALKT_RIP_PI1_counts_lnc$lib + ALKT_RIP_PI1_counts_lnc$lib
ALKT_RIP_PI_d <- DGEList(counts=as.matrix(ALKT_RIP_PI_counts_lnc), lib.size=ALKT_RIP_PI_lib_lnc)
ALKT_RIP_PI_rpkm <- data.frame(rpkm(ALKT_RIP_PI_d,width(lnc_tx)))
ALKT_RIP_PARP_d <- DGEList(counts=as.matrix(ALKT_RIP_PARP_counts_lnc), lib.size=ALKT_RIP_PARP_lib_lnc)
ALKT_RIP_PARP_rpkm <- data.frame(rpkm(ALKT_RIP_PARP_d,width(lnc_tx)))
ALKT_RIP_FC <- data.frame((ALKT_RIP_PARP_rpkm+1)/(ALKT_RIP_PI_rpkm+1))
alkt_lnc_rpkm_fc <- lnc_tx[ALKT_RNA_lnc_rpkm>=1 & ALKT_RIP_FC>=2 ]
NROW(unique(unlist(mcols(alkt_lnc_rpkm_fc)$tx_name)))
NROW(unique(unlist(mcols(alkt_lnc_rpkm_fc)$gene_id)))
lnc_ratio <- NROW(unique(unlist(mcols(alkt_lnc_rpkm_fc)$gene_id)))/NROW(unique(unlist(mcols(alkt_lnc_rpkm)$gene_id)))
ALKT_RNA_counts_sno <- ALKT_RNA1_counts_sno$counts + ALKT_RNA2_counts_sno$counts
ALKT_RNA_lib_sno <- ALKT_RNA1_counts_sno$lib + ALKT_RNA1_counts_sno$lib
ALKT_RNA_sno_d <- DGEList(counts=as.matrix(ALKT_RNA_counts_sno), lib.size=ALKT_RNA_lib_sno)
ALKT_RNA_sno_rpkm <- data.frame(rpkm(ALKT_RNA_sno_d,width(sno_tx)))
alkt_sno_rpkm <- sno_tx[ALKT_RNA_sno_rpkm>=1]
NROW(unique(unlist(mcols(alkt_sno_rpkm)$tx_name)))
ALKT_RIP_PARP_counts_sno <- ALKT_RIP_PARP1_counts_sno$counts + ALKT_RIP_PARP2_counts_sno$counts
ALKT_RIP_PARP_lib_sno<- ALKT_RIP_PARP1_counts_sno$lib + ALKT_RIP_PARP2_counts_sno$lib
ALKT_RIP_PI_counts_sno <- ALKT_RIP_PI1_counts_sno$counts + ALKT_RIP_PI2_counts_sno$counts
ALKT_RIP_PI_lib_sno <- ALKT_RIP_PI1_counts_sno$lib + ALKT_RIP_PI1_counts_sno$lib
ALKT_RIP_PI_d <- DGEList(counts=as.matrix(ALKT_RIP_PI_counts_sno), lib.size=ALKT_RIP_PI_lib_sno)
ALKT_RIP_PI_rpkm <- data.frame(rpkm(ALKT_RIP_PI_d,width(sno_tx)))
ALKT_RIP_PARP_d <- DGEList(counts=as.matrix(ALKT_RIP_PARP_counts_sno), lib.size=ALKT_RIP_PARP_lib_sno)
ALKT_RIP_PARP_rpkm <- data.frame(rpkm(ALKT_RIP_PARP_d,width(sno_tx)))
ALKT_RIP_FC <- data.frame((ALKT_RIP_PARP_rpkm+1)/(ALKT_RIP_PI_rpkm+1))
alkt_sno_rpkm_fc <- sno_tx[ALKT_RNA_sno_rpkm>=1 & ALKT_RIP_FC>=2 ]
NROW(unique(unlist(mcols(alkt_sno_rpkm_fc)$tx_name)))
sno_ratio <- NROW(unique(unlist(mcols(alkt_sno_rpkm_fc)$tx_name)))/NROW(unique(unlist(mcols(alkt_sno_rpkm)$tx_name)))
ALKT_RIP_sno <- data.frame(ALKT_RIP_PI_rpkm,ALKT_RIP_PARP_rpkm)
colnames(ALKT_RIP_sno) <- c('PI', 'PARP1')
ALKT_RIP_sno_rpkm <- ALKT_RIP_sno[ALKT_RNA_sno_rpkm>=1 & ALKT_RIP_FC>=2,]
ALKT_RNA_counts_sn <- ALKT_RNA1_counts_sn$counts + ALKT_RNA2_counts_sn$counts
ALKT_RNA_lib_sn <- ALKT_RNA1_counts_sn$lib + ALKT_RNA1_counts_sn$lib
ALKT_RNA_sn_d <- DGEList(counts=as.matrix(ALKT_RNA_counts_sn), lib.size=ALKT_RNA_lib_sn)
ALKT_RNA_sn_rpkm <- data.frame(rpkm(ALKT_RNA_sn_d,width(sn_tx)))
alkt_sn_rpkm <- sn_tx[ALKT_RNA_sn_rpkm>=1]
NROW(unique(unlist(mcols(alkt_sn_rpkm)$tx_name)))
ALKT_RIP_PARP_counts_sn <- ALKT_RIP_PARP1_counts_sn$counts + ALKT_RIP_PARP2_counts_sn$counts
ALKT_RIP_PARP_lib_sn<- ALKT_RIP_PARP1_counts_sn$lib + ALKT_RIP_PARP2_counts_sn$lib
ALKT_RIP_PI_counts_sn <- ALKT_RIP_PI1_counts_sn$counts + ALKT_RIP_PI2_counts_sn$counts
ALKT_RIP_PI_lib_sn <- ALKT_RIP_PI1_counts_sn$lib + ALKT_RIP_PI1_counts_sn$lib
ALKT_RIP_PI_d <- DGEList(counts=as.matrix(ALKT_RIP_PI_counts_sn), lib.size=ALKT_RIP_PI_lib_sn)
ALKT_RIP_PI_rpkm <- data.frame(rpkm(ALKT_RIP_PI_d,width(sn_tx)))
ALKT_RIP_PARP_d <- DGEList(counts=as.matrix(ALKT_RIP_PARP_counts_sn), lib.size=ALKT_RIP_PARP_lib_sn)
ALKT_RIP_PARP_rpkm <- data.frame(rpkm(ALKT_RIP_PARP_d,width(sn_tx)))
ALKT_RIP_FC <- data.frame((ALKT_RIP_PARP_rpkm+1)/(ALKT_RIP_PI_rpkm+1))
alkt_sn_rpkm_fc <- sn_tx[ALKT_RNA_sn_rpkm>=1 & ALKT_RIP_FC>=2 ]
NROW(unique(unlist(mcols(alkt_sn_rpkm_fc)$tx_name)))
sn_ratio <- NROW(unique(unlist(mcols(alkt_sn_rpkm_fc)$tx_name)))/NROW(unique(unlist(mcols(alkt_sn_rpkm)$tx_name)))
ALKT_RIP_sn <- data.frame(ALKT_RIP_PI_rpkm,ALKT_RIP_PARP_rpkm)
colnames(ALKT_RIP_sn) <- c('PI', 'PARP1')
ALKT_RIP_sn_rpkm <- ALKT_RIP_sn[ALKT_RNA_sn_rpkm>=1 & ALKT_RIP_FC>=2,]
alkt_allsno <- c(alkt_sno_rpkm_fc,alkt_sn_rpkm_fc)
alkt_allsno_rpkm <- rbind(ALKT_RIP_sno_rpkm,ALKT_RIP_sn_rpkm)
allsno_rna <- c(sno_tx,sn_tx)
alkt_allsno_rna_rpkm <- rbind(ALKT_RNA_sno_rpkm,ALKT_RNA_sn_rpkm)
# bar plot figure (B)
# Grouped Bar Plot
jpeg('barchart-ac16-tnf-species.jpg')
ratios <- c(pc_ratio,lnc_ratio,sno_ratio,sn_ratio)
barplot(ratios, main="SNORNA AC16 TNF", col=c("red","black", "dimgrey", "lightgrey"),ylim=c(0,.5))
dev.off()
boundTesting <-matrix(c(1644,5047,225,249),nrow = 2,dimnames = list(Guess = c("bound", "unbound"),Truth = c("mRNA", "snoRNA")))
fisher.test(boundTesting)
# Boxplot of Preimmune vs PARP-1 (C)
jpeg('boxplot-ac16-tnf-species.jpg')
boxplot(ALKT_RIP_sno_rpkm,col=(c("orange","blue")),outline=FALSE,ylim = c(0,400),yaxt="n", cex.axis=1,las=2,lwd=4,lty=1)
axis(2, at=seq(0,400,100))
dev.off()
wilcox.test(ALKT_RIP_sno_rpkm[,1], ALKT_RIP_sno_rpkm[,2],paired=T)
# Get Categories of snoRNA
alkt_gr_snotx <- data.frame(seqnames=seqnames(alkt_sno_rpkm),
starts=start(alkt_sno_rpkm)-1,
ends=end(alkt_sno_rpkm),
strand=strand(alkt_sno_rpkm),
tx_name = elementMetadata(alkt_sno_rpkm)$tx_name,
gene_id = unlist(elementMetadata(alkt_sno_rpkm)$gene_id))
sno_annotations <- read.table('RNA_small_nucleolar.txt',header = TRUE, sep = "\t")
sno_inx <- match(matrix(unlist(strsplit(as.character(alkt_gr_snotx$gene_id),split='.',fixed=T)),ncol=2,byrow=T)[,1], sno_annotations$ensembl_gene_id)
alkt_gr_snotx$symbol <- as.character(sno_annotations[sno_inx,"symbol"])
alkt_gr_snotx$gene_family <- as.character(sno_annotations[sno_inx,"gene_family"])
alkt_gr_snotx$gene_family[alkt_gr_snotx$gene_family == "Small nucleolar RNAs, H/ACA box"] <- "H/ACA box"
alkt_gr_snotx$gene_family[alkt_gr_snotx$gene_family == "Small nucleolar RNAs, C/D box"] <- "C/D box"
alkt_gr_snotx$gene_family[alkt_gr_snotx$gene_family == "Small Cajal body-specific RNAs"] <- "scaRNA"
alkt_gr_snotx$gene_family[alkt_gr_snotx$gene_family == ""] <- "Other"
alkt_gr_snotx$gene_family[is.na(alkt_gr_snotx$gene_family)] <- "Other"
ha_rna <- dim(alkt_gr_snotx[alkt_gr_snotx$gene_family == "H/ACA box",])[1]
cd_rna <- dim(alkt_gr_snotx[alkt_gr_snotx$gene_family == "C/D box",])[1]
sc_rna <- dim(alkt_gr_snotx[alkt_gr_snotx$gene_family == "scaRNA",])[1]
dat = data.frame(count=c(ha_rna, cd_rna, sc_rna), category=c("H/ACA box", "C/D box", "scaRNA"))
dat$fraction = dat$count / sum(dat$count)
dat$ymax = cumsum(dat$fraction)
dat$ymin = c(0, head(dat$ymax, n=-1))
dat$category <- factor(dat$category, levels = c("H/ACA box", "C/D box", "scaRNA"))
# (E)
jpeg('piechart-ac16-tnf-species.jpg')
ggplot(dat, aes(fill=category, ymax=ymax, ymin=ymin, xmax=4, xmin=2)) +
geom_rect(fill=c('darkorchid1', "darkorange1","darkgreen")) +
coord_polar(theta="y") +
xlim(c(0, 4)) +
theme_bw() +
theme(panel.grid=element_blank()) +
theme(axis.text=element_blank()) +
theme(axis.ticks=element_blank())
dev.off()
alkt_gr_snotx <- data.frame(seqnames=seqnames(alkt_sno_rpkm_fc),
starts=start(alkt_sno_rpkm_fc)-1,
ends=end(alkt_sno_rpkm_fc),
strand=strand(alkt_sno_rpkm_fc),
tx_name = elementMetadata(alkt_sno_rpkm_fc)$tx_name,
gene_id = unlist(elementMetadata(alkt_sno_rpkm_fc)$gene_id))
sno_inx <- match(matrix(unlist(strsplit(as.character(alkt_gr_snotx$gene_id),split='.',fixed=T)),ncol=2,byrow=T)[,1], sno_annotations$ensembl_gene_id)
alkt_gr_snotx$symbol <- as.character(sno_annotations[sno_inx,"symbol"])
alkt_gr_snotx$gene_family <- as.character(sno_annotations[sno_inx,"gene_family"])
alkt_gr_snotx$gene_family[alkt_gr_snotx$gene_family == "Small nucleolar RNAs, H/ACA box"] <- "H/ACA box"
alkt_gr_snotx$gene_family[alkt_gr_snotx$gene_family == "Small nucleolar RNAs, C/D box"] <- "C/D box"
alkt_gr_snotx$gene_family[alkt_gr_snotx$gene_family == "Small Cajal body-specific RNAs"] <- "scaRNA"
alkt_gr_snotx$gene_family[alkt_gr_snotx$gene_family == ""] <- "Other"
alkt_gr_snotx$gene_family[is.na(alkt_gr_snotx$gene_family)] <- "Other"
ha_rip <- dim(alkt_gr_snotx[alkt_gr_snotx$gene_family == "H/ACA box",])[1]
cd_rip <- dim(alkt_gr_snotx[alkt_gr_snotx$gene_family == "C/D box",])[1]
sc_rip<- dim(alkt_gr_snotx[alkt_gr_snotx$gene_family == "scaRNA",])[1]
# bar plot figure (F)
# Bar plot
jpeg('barchart-ac16-tnf-species_snospecies.jpg')
ratios <- c(sn_ratio,ha_rip/ha_rna,cd_rip/cd_rna,sc_rip/sc_rna)
barplot(ratios, main="snoRNA species AC16 TNF", col=c('pink1','darkorchid1', "darkorange1","darkgreen"),ylim=c(0,1))
dev.off()
typeTesting <-matrix(c(68,14,61,98),nrow = 2,dimnames = list(Guess = c("bound", "unbound"),Truth = c("HA", "CD")))
fisher.test(typeTesting)
# Combine snRNA and snoRNA and print out
allsnotx_tnf <- data.frame(seqnames=seqnames(alkt_allsno),
starts=start(alkt_allsno)-1,
ends=end(alkt_allsno),
strand=strand(alkt_allsno),
tx_id = elementMetadata(alkt_allsno)$tx_name,
gene_id = unlist(elementMetadata(alkt_allsno)$gene_id))
allsnotx_tnf_rpkm <- cbind(allsnotx_tnf,alkt_allsno_rpkm)
sno_mapping <- read.csv("./gencode.v19.annotation_snoRNA_mapping.txt", header=F, sep=',')
sn_mapping <- read.csv("./gencode.v19.annotation_snRNA_mapping.txt", header=F, sep=',')
gencode_sn_mapping <-rbind(sno_mapping,sn_mapping)
sn_inx <- match(allsnotx_tnf_rpkm$tx_id, gencode_sn_mapping$V2)
allsnotx_tnf_rpkm$tx_name <- as.character(gencode_sn_mapping[sn_inx,"V4"])
allsnotx_tnf_rpkm$gene_name <- as.character(gencode_sn_mapping[sn_inx,"V3"])
write.table(allsnotx_tnf_rpkm, file="ac16-tnf-snRNA_RPKM_1_FC_2.tsv", quote=F, sep="\t", row.names=F, col.names=T)
allsnotx_rna <- data.frame(seqnames=seqnames(allsno_rna),
starts=start(allsno_rna)-1,
ends=end(allsno_rna),
strand=strand(allsno_rna),
tx_id = elementMetadata(allsno_rna)$tx_name,
gene_id = unlist(elementMetadata(allsno_rna)$gene_id))
alkt_allsnotx_rna_rpkm <- cbind(allsnotx_rna,alkt_allsno_rna_rpkm)
sno_mapping <- read.csv("./gencode.v19.annotation_snoRNA_mapping.txt", header=F, sep=',')
sn_mapping <- read.csv("./gencode.v19.annotation_snRNA_mapping.txt", header=F, sep=',')
gencode_sn_mapping <-rbind(sno_mapping,sn_mapping)
sn_inx <- match(alkt_allsnotx_rna_rpkm$tx_id, gencode_sn_mapping$V2)
alkt_allsnotx_rna_rpkm$tx_name <- as.character(gencode_sn_mapping[sn_inx,"V4"])
alkt_allsnotx_rna_rpkm$gene_name <- as.character(gencode_sn_mapping[sn_inx,"V3"])
write.table(alkt_allsnotx_rna_rpkm, file="ac16-tnf-snRNA_RPKM_RNA.tsv", quote=F, sep="\t", row.names=F, col.names=T)
```
# Overlap of snoRNA and snRNA
``` {r snoRNA Overlap}
# Overlap (A)
ac16_unique <- unique(alk_gr_snotx$tx_name)
tnf_unique <- unique(alkt_gr_snotx$tx_name)
overlap <- calculate.overlap(x = list("Basal" = ac16_unique,"TNF" = tnf_unique))
jpeg('venndigram_basal_tnf_snoRNA.jpg')
draw.pairwise.venn(area1 = length(overlap$a1), area2 = length(overlap$a2), cross.area = length(overlap$a3),col = c("royalblue4", "seagreen4"),lwd=4)
dev.off()
```
Summary_RIP-seq.xlsx
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ac16-tnf-snRNA_RPKM_1_FC_2.tsv 0 → 100644
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correlations.pptx
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