All the Pre-build PAS reference regions are stored at here, currently support mm9, mm10, hg19, and hg38
Sample file are only need when Reps='YES'. This file is a two-column table contain the information of the sample and group. For instance, in the above case, the sample file should looks like:
| File name | Genome | Note |
|---|---|---|
| hg19_REF.RData | hg19 | Conserved 3'UTR PAS and highly used IPA from PolyA_DB3 |
| hg19_REF_ALL.RData | hg19 | All 3'UTR PAS and IPA from PolyA_DB3 |
| hg38_REF.RData | hg38 | Conserved 3'UTR PAS and highly used IPA from PolyA_DB3 |
| mm9_REF.RData | mm9 | Conserved 3'UTR PAS and highly used IPA from PolyA_DB3 |
| mm9_REF_ALL.RData | mm9 | All 3'UTR PAS and IPA from PolyA_DB3 |
| mm10_REF.RData | mm10 | Conserved 3'UTR PAS and highly used IPA from PolyA_DB3 |
library(repmis)
URL="https://github.com/RJWANGbioinfo/PAS_reference_RData/blob/master/"
file="hg19_REF.RData"
source_data(paste0(URL,file,"?raw=True"))
To provide a complete tutorial of APA analysis using our package, we have now prepared a testing dataset through down sampling of mouse RNA-Seq data in heart (GSM900193) and testis (GSM900199):
| Sample ID | SRRID | Sample Name | Down sampling reads |
|---|---|---|---|
| GSM900199 | SRR453175 | Heart_Rep1 | 5 Million |
| GSM900199 | SRR453174 | Heart_Rep2 | 5 Million |
| GSM900199 | SRR453173 | Heart_Rep3 | 5 Million |
| GSM900199 | SRR453172 | Heart_Rep4 | 5 Million |
| GSM900193 | SRR453143 | Testis_rep1 | 5 Million |
| GSM900193 | SRR453142 | Testis_rep2 | 5 Million |
| GSM900193 | SRR453141 | Testis_rep3 | 5 Million |
| GSM900193 | SRR453140 | Testis_rep4 | 5 Million |
library(APAlyzer)
download_testbam()
flsall <- dir(getwd(),".bam")
flsall<-paste0(getwd(),'/',flsall)
names(flsall)<-gsub('.bam','',dir(getwd(),".bam"))