| Title: | Pooling RNA-seq datasets for assembling transcript models |
|---|---|
| Description: | Publicly available RNA-seq data is routinely used for retrospective analysis to elucidate new biology. Novel transcript discovery enabled by large collections of RNA-seq datasets has emerged as one of such analysis. To increase the power of transcript discovery from large collections of RNA-seq datasets, we developed a new R package named Pooling RNA-seq and Assembling Models (PRAM), which builds transcript models in intergenic regions from pooled RNA-seq datasets. This package includes functions for defining intergenic regions, extracting and pooling related RNA-seq alignments, predicting, selected, and evaluating transcript models. |
| Authors: | Peng Liu [aut, cre], Colin N. Dewey [aut], Sündüz Keleş [aut] |
| Maintainer: | Peng Liu <[email protected]> |
| License: | GPL (>= 3) |
| Version: | 1.23.0 |
| Built: | 2024-11-03 06:23:34 UTC |
| Source: | https://github.com/bioc/pram |
Build transcript models from aligned RNA-seq data
buildModel(in_bamv, out_gtf, method = "plcf", nthreads = 1, tmpdir = NULL, keep_tmpdir = FALSE, cufflinks = "", stringtie = "", taco = "", cufflinks_ref_fa = "")buildModel(in_bamv, out_gtf, method = "plcf", nthreads = 1, tmpdir = NULL, keep_tmpdir = FALSE, cufflinks = "", stringtie = "", taco = "", cufflinks_ref_fa = "")
in_bamv |
A character vector of input BAM file(s). If mode 'cf' or 'st' is used, only one input RNA-seq BAM file is allowed. Currently, PRAM only supports strand-specific paired-end data with the first mate on the right-most of transcript coordinate, i.e., 'fr-firststrand' by Cufflinks's definition. |
out_gtf |
An output GTF file of predicted transcript models |
method |
A character string defining PRAM's model building method. Current available methods are:
Default: 'plcf' |
nthreads |
An integer defining the number of threads to-be-used. Default: 1 |
tmpdir |
A character string defining the full name of a folder for saving temporary files. If not tmpdir is give, PRAM will use R's tempdir(). |
keep_tmpdir |
Whether to keep temporary files afterwards. Default: False |
cufflinks |
Cufflinks executable. Required by mode 'plcf', 'cfmg', and 'cf'. For mode 'cfmg', executable files of Cuffmerge, Cuffcompare, and gtf_to_sam from the Cufflinks suite are assumed to be under the same folder as Cufflinks. All the executables are available to download for Linux http://cole-trapnell-lab.github.io/cufflinks/assets/downloads/cufflinks-2.2.1.Linux_x86_64.tar.gz and MacOS http://cole-trapnell-lab.github.io/cufflinks/assets/downloads/cufflinks-2.1.1.OSX_x86_64.tar.gz. Souce code can be obtained from http://cole-trapnell-lab.github.io/cufflinks/. Default: ” |
stringtie |
StringTie executable file. Required by mode 'plst', 'stmg', and 'st'. Executable can be downloaded for Linux http://ccb.jhu.edu/software/stringtie/dl/stringtie-1.3.3b.Linux_x86_64.tar.gz and MacOS http://ccb.jhu.edu/software/stringtie/dl/stringtie-1.3.3b.OSX_x86_64.tar.gz. Souce code can be obtained from https://ccb.jhu.edu/software/stringtie/. Default: ” |
taco |
TACO executable file. Required by mode 'cftc'. Executable can be downloaded for Linux https://github.com/tacorna/taco/releases/download/v0.7.0/taco-v0.7.0.Linux_x86_64.tar.gz and MacOS https://github.com/tacorna/taco/releases/download/v0.7.0/taco-v0.7.0.OSX_x86_64.tar.gz. Souce code can be obtained from https://tacorna.github.io. Default: ” |
cufflinks_ref_fa |
Genome reference fasta file for Cufflinks. If supplied, will be used for cufflinks's '–frag-bias-correct' and cuffmerge's '–ref-sequence' options. Default: ” |
None
fbams = c( system.file('extdata/bam/CMPRep1.sortedByCoord.clean.bam', package='pram'), system.file('extdata/bam/CMPRep2.sortedByCoord.clean.bam', package='pram') ) foutgtf = tempfile(fileext='.gtf') ## assuming the stringtie binary is in folder /usr/local/stringtie-1.3.3/ ## you can run buildModel() by the following example ## # buildModel(fbams, foutgtf, method='plst', # stringtie='/usr/local/stringtie-1.3.3/stringtie')fbams = c( system.file('extdata/bam/CMPRep1.sortedByCoord.clean.bam', package='pram'), system.file('extdata/bam/CMPRep2.sortedByCoord.clean.bam', package='pram') ) foutgtf = tempfile(fileext='.gtf') ## assuming the stringtie binary is in folder /usr/local/stringtie-1.3.3/ ## you can run buildModel() by the following example ## # buildModel(fbams, foutgtf, method='plst', # stringtie='/usr/local/stringtie-1.3.3/stringtie')
Define intergenic genomic regions
defIgRanges(in_gtf, chromgrs, genome = NULL, fchromsize = NULL, radius = 10000, feat = "exon", chroms = NULL)defIgRanges(in_gtf, chromgrs, genome = NULL, fchromsize = NULL, radius = 10000, feat = "exon", chroms = NULL)
in_gtf |
An input GTF file for defining genomic coordinates of existing genes. Required to have 'gene_id' in the attribute column (column 9) |
chromgrs |
A GRanges object defining chromosome sizes. |
genome |
Version of the genome. Will be used when 'chromgrs' is missing. Currently supported ones are:
All the above genomes have sizes for all chromosomes including random and alt ones. Default: NULL |
fchromsize |
Name of a file defining chromosome sizes. Will be used when 'chromgrs' and 'genome' are missing. It can be downloaded from UCSC, e.g. for hg19, http://hgdownload.cse.ucsc.edu/ goldenpath/hg19/database/chromInfo.txt.gz Required to have at least two tab-delimited columns without any header:
Both uncompressed and gzipped files are supported. Default: NULL |
radius |
Region length (bp) of gene's upstream and downstream to be excluded from intergenic region. Default: 10,000 |
feat |
Feature in the GTF file (column 3) to-be-used for defining genic region. Default: exon |
chroms |
A vector of chromosomes names to define intergenic regions. e.g. c('chr10', 'chr11') Default: NULL |
a GRanges object of intergenic regions
fgtf = system.file('extdata/gtf/defIgRanges_in.gtf', package='pram') defIgRanges(fgtf, genome='hg38')fgtf = system.file('extdata/gtf/defIgRanges_in.gtf', package='pram') defIgRanges(fgtf, genome='hg38')
Evaluate trascript model's precision and recall on exon nucleotides, splice junctions, and splice patterns by comparing them to transcript targets
evalModel(model_exons, target_exons) ## S4 method for signature 'GRanges,GRanges' evalModel(model_exons, target_exons) ## S4 method for signature 'character,character' evalModel(model_exons, target_exons) ## S4 method for signature 'data.table,data.table' evalModel(model_exons, target_exons) ## S4 method for signature 'character,data.table' evalModel(model_exons, target_exons)evalModel(model_exons, target_exons) ## S4 method for signature 'GRanges,GRanges' evalModel(model_exons, target_exons) ## S4 method for signature 'character,character' evalModel(model_exons, target_exons) ## S4 method for signature 'data.table,data.table' evalModel(model_exons, target_exons) ## S4 method for signature 'character,data.table' evalModel(model_exons, target_exons)
model_exons |
genomic coordinates for transcript model exons |
target_exons |
genomic coordinates for transcript target exons |
a data table of precision, recall, number of true positive, false negative, false positive for all three evaluated features
model_exons = GRanges,target_exons = GRanges: Both
model_exons and target_exons
are GRanges objects
to define genomic coordinates of exons. Required to
have a meta-data column named 'trid' to define each
exon's transcript ID.
model_exons = character,target_exons = character: Both
model_exons and target_exons
are GTF files with full names. Each GTF file is
required to have a 'transcript_id' tag in column 9.
model_exons = data.table,target_exons = data.table: Both
model_exons and target_exons
are data.table objects to define exon genomic
coordinatess. Required to have the following columns:
chrom: exon's chromosome, e.g. 'chr8'
start: exon's start position
end: exon's end position
strand: exon's strand, '+' or '-'
trid: exon's transcript ID
model_exons = character,target_exons = data.table: The
model_exons is a GTF file with full
name and target_exons is a data.table object.
Requirements for GTF and data.table are the same as
above
fmdl = system.file('extdata/benchmark/plcf.tsv', package='pram') ftgt = system.file('extdata/benchmark/tgt.tsv', package='pram') mdldt = data.table::fread(fmdl, header=TRUE, sep="\t") tgtdt = data.table::fread(ftgt, header=TRUE, sep="\t") evalModel(mdldt, tgtdt)fmdl = system.file('extdata/benchmark/plcf.tsv', package='pram') ftgt = system.file('extdata/benchmark/tgt.tsv', package='pram') mdldt = data.table::fread(fmdl, header=TRUE, sep="\t") tgtdt = data.table::fread(ftgt, header=TRUE, sep="\t") evalModel(mdldt, tgtdt)
Extract alignments in intergenic regions from BAM files
prepIgBam(finbam, iggrs, foutbam, max_uni_n_dup_aln = 10, max_mul_n_dup_aln = 10)prepIgBam(finbam, iggrs, foutbam, max_uni_n_dup_aln = 10, max_mul_n_dup_aln = 10)
finbam |
Full name of an input RNA-seq BAM file. Currently, PRAM only supports strand-specific paired-end data with the first mate on the right-most of transcript coordinate, i.e., 'fr-firststrand' by Cufflinks's definition |
iggrs |
A GenomicRanges object defining intergenic regions |
foutbam |
Full name of an output BAM file to save all alignment fell into intergenic regions |
max_uni_n_dup_aln |
Maximum number of uniquely mapped fragments to report per each alignment. Default: 10 |
max_mul_n_dup_aln |
Maximum number of multi-mapping fragments to report per each alignment. Default: 10 |
None
finbam = system.file('extdata/bam/CMPRep2.sortedByCoord.raw.bam', package='pram') iggrs = GenomicRanges::GRanges('chr10:77236000-77247000:+') foutbam = tempfile(fileext='.bam') prepIgBam(finbam, iggrs, foutbam)finbam = system.file('extdata/bam/CMPRep2.sortedByCoord.raw.bam', package='pram') iggrs = GenomicRanges::GRanges('chr10:77236000-77247000:+') foutbam = tempfile(fileext='.bam') prepIgBam(finbam, iggrs, foutbam)
Predict intergenic transcript models from RNA-seq
runPRAM(in_gtf, in_bamv, out_gtf, method, cufflinks = "", stringtie = "", taco = "")runPRAM(in_gtf, in_bamv, out_gtf, method, cufflinks = "", stringtie = "", taco = "")
in_gtf |
An input GTF file for defining genomic coordinates of existing genes. Required to have 'gene_id' in the attribute column (column 9) |
in_bamv |
A character vector of input BAM file(s). If mode 'cf' or 'st' is used, only one input RNA-seq BAM file is allowed. Currently, PRAM only supports strand-specific paired-end data with the first mate on the right-most of transcript coordinate, i.e., 'fr-firststrand' by Cufflinks's definition. |
out_gtf |
An output GTF file of predicted transcript models |
method |
A character string defining PRAM's model building method. Current available methods are:
Default: 'plcf' |
cufflinks |
Cufflinks executable. Required by mode 'plcf', 'cfmg', and 'cf'. For mode 'cfmg', executable files of Cuffmerge, Cuffcompare, and gtf_to_sam from the Cufflinks suite are assumed to be under the same folder as Cufflinks. All the executables are available to download for Linux http://cole-trapnell-lab.github.io/cufflinks/assets/downloads/cufflinks-2.2.1.Linux_x86_64.tar.gz and MacOS http://cole-trapnell-lab.github.io/cufflinks/assets/downloads/cufflinks-2.1.1.OSX_x86_64.tar.gz. Souce code can be obtained from http://cole-trapnell-lab.github.io/cufflinks/. Default: ” |
stringtie |
StringTie executable file. Required by mode 'plst', 'stmg', and 'st'. Executable can be downloaded for Linux http://ccb.jhu.edu/software/stringtie/dl/stringtie-1.3.3b.Linux_x86_64.tar.gz and MacOS http://ccb.jhu.edu/software/stringtie/dl/stringtie-1.3.3b.OSX_x86_64.tar.gz. Souce code can be obtained from https://ccb.jhu.edu/software/stringtie/. Default: ” |
taco |
TACO executable file. Required by mode 'cftc'. Executable can be downloaded for Linux https://github.com/tacorna/taco/releases/download/v0.7.0/taco-v0.7.0.Linux_x86_64.tar.gz and MacOS https://github.com/tacorna/taco/releases/download/v0.7.0/taco-v0.7.0.OSX_x86_64.tar.gz. Souce code can be obtained from https://tacorna.github.io. Default: ” |
None
in_gtf = system.file('extdata/demo/in.gtf', package='pram') in_bamv = c(system.file('extdata/demo/SZP.bam', package='pram'), system.file('extdata/demo/TLC.bam', package='pram') ) pred_out_gtf = tempfile(fileext='.gtf') ## assuming the stringtie binary is in folder /usr/local/stringtie-1.3.3/ ## you can run runPRAM() by the following example ## # runPRAM(in_gtf, in_bamv, pred_out_gtf, method='plst', # stringtie='/usr/local/stringtie-1.3.3/stringtie')in_gtf = system.file('extdata/demo/in.gtf', package='pram') in_bamv = c(system.file('extdata/demo/SZP.bam', package='pram'), system.file('extdata/demo/TLC.bam', package='pram') ) pred_out_gtf = tempfile(fileext='.gtf') ## assuming the stringtie binary is in folder /usr/local/stringtie-1.3.3/ ## you can run runPRAM() by the following example ## # runPRAM(in_gtf, in_bamv, pred_out_gtf, method='plst', # stringtie='/usr/local/stringtie-1.3.3/stringtie')
Select transcript models
selModel(fin_gtf, fout_gtf, min_n_exon = 2, min_tr_len = 200, info_keys = c("transcript_id"))selModel(fin_gtf, fout_gtf, min_n_exon = 2, min_tr_len = 200, info_keys = c("transcript_id"))
fin_gtf |
Character of an input GTF file that contains transcript models. Required to have 'transcript_id' in the attribute column (column 9) |
fout_gtf |
Character of an output GTF file that contains selected transcript models |
min_n_exon |
Minimium number of exons a transcript model required to have Default: 2 |
min_tr_len |
Minimium length (bp) of exon(s) and intron(s) a transcript model required to have Default: 200 |
info_keys |
A vector of characters defining the attributes in input GTF file's column 9 to be saved in the output GTF file. 'transcript_id' will always be saved. Default: c( 'transcript_id' ) |
None
fin_gtf = system.file('extdata/gtf/selModel_in.gtf', package='pram') fout_gtf = tempfile(fileext='.gtf') selModel(fin_gtf, fout_gtf)fin_gtf = system.file('extdata/gtf/selModel_in.gtf', package='pram') fout_gtf = tempfile(fileext='.gtf') selModel(fin_gtf, fout_gtf)