| Title: | Aligned reads from RNAseq experiment: Transcription profiling by high throughput sequencing of HNRNPC knockdown and control HeLa cells |
|---|---|
| Description: | The package contains 8 BAM files, 1 per sequencing run. Each BAM file was obtained by (1) aligning the reads (paired-end) to the full hg19 genome with TopHat2, and then (2) subsetting to keep only alignments on chr14. See accession number E-MTAB-1147 in the ArrayExpress database for details about the experiment, including links to the published study (by Zarnack et al., 2012) and to the FASTQ files. |
| Authors: | Hervé Pagès |
| Maintainer: | Hervé Pagès <[email protected]> |
| License: | LGPL |
| Version: | 0.50.0 |
| Built: | 2026-10-10 11:04:53 UTC |
| Source: | https://github.com/bioc/RNAseqData.HNRNPC.bam.chr14 |
The package contains 8 BAM files, 1 per sequencing run. Each BAM file was obtained by (1) aligning the reads (paired-end) to the full hg19 genome with TopHat2, and then (2) subsetting to keep only alignments on chr14. See accession number E-MTAB-1147 in the ArrayExpress database for details about the experiment, including links to the published study (by Zarnack et al., 2012) and to the FASTQ files.
RNAseqData.HNRNPC.bam.chr14_RUNNAMES is a predefined character vector
containing the names of the 8 runs of the RNAseq experiment. The name of
each run is its accession number on the European Nucleotide Archive (ENA).
RNAseqData.HNRNPC.bam.chr14_BAMFILES is a predefined named character
vector of length 8 containing the paths to the 8 BAM files obtained by
aligning the reads from each sequencing run. The reads were aligned to the
full hg19 genome with TopHat2 and then the resulting BAM file was subset
to keep only alignments located on chr14.
RNAseqData.HNRNPC.bam.chr14_RUNNAMES RNAseqData.HNRNPC.bam.chr14_BAMFILESRNAseqData.HNRNPC.bam.chr14_RUNNAMES RNAseqData.HNRNPC.bam.chr14_BAMFILES
The scripts/ folder in the package contains the scripts that were used to generate the data contained in the package (note that all the data contained in the package is located in its extdata/ folder). The README.TXT file in the scripts/ folder describes how to use those scripts to re-generate the data.
Direct Competition between hnRNP C and U2AF65 Protects the Transcriptome from the Exonization of Alu Elements. Kathi Zarnack, Julian Konig, Mojca Tajnik, Inigo Martincorena, Sebastian Eustermann, Isabelle Stevant, Alejandro Reyes, Simon Anders, Nicholas M. Luscombe, Jernej Ule. Cell 2012, Europe PMC 23374342
TopHat2: accurate alignment of transcriptomes in the presence of insertions, deletions and gene fusions. Daehwan Kim, Geo Pertea, Cole Trapnell, Harold Pimentel, Ryan Kelley and Steven L Salzberg. Genome biology 2013, 14:R36
http://www.ebi.ac.uk/arrayexpress/experiments/E-MTAB-1147/ for details about the experiment, including links to the published study (by Kathi Zarnack et al., 2012) and to the FASTQ files.
http://www.ebi.ac.uk/ena/data/view/ERR127306, http://www.ebi.ac.uk/ena/data/view/ERR127307, http://www.ebi.ac.uk/ena/data/view/ERR127308, http://www.ebi.ac.uk/ena/data/view/ERR127309, http://www.ebi.ac.uk/ena/data/view/ERR127302, http://www.ebi.ac.uk/ena/data/view/ERR127303, http://www.ebi.ac.uk/ena/data/view/ERR127304, and http://www.ebi.ac.uk/ena/data/view/ERR127305, for direct access to individual runs on the European Nucleotide Archive (ENA).
http://ccb.jhu.edu/software/tophat for the TopHat2 software.
http://samtools.sourceforge.net/SAM1.pdf for the SAM Format Specification.
The readGAlignmentPairs function
in the GenomicAlignments package for more information about
how to read paired-end reads from a BAM file into Bioconductor.
The ScanBamParam function in the
Rsamtools package for how to get control over what to
import from a BAM file.
RNAseqData.HNRNPC.bam.chr14_RUNNAMES RNAseqData.HNRNPC.bam.chr14_BAMFILES if (require(GenomicAlignments)) { bamfiles <- RNAseqData.HNRNPC.bam.chr14_BAMFILES param <- ScanBamParam(tag="NM") galp <- readGAlignmentPairs(bamfiles[1L], use.names=TRUE, param=param) galp first(galp) # 1st segment in each pair last(galp) # 2nd segment in each pair ## The alignments contain insertions, deletions, and junctions (I, D, ## and N CIGAR operations, respectively): colSums(cigarOpTable(cigar(first(galp)))) colSums(cigarOpTable(cigar(last(galp)))) ## njunc() returns the nb of junctions for each alignment: table(njunc(first(galp))) table(njunc(last(galp))) table(njunc(first(galp)) + njunc(last(galp))) # up to 5 junctions # per pair! ## The NM tag gives the edit distance of each alignment to the ## reference (ignoring the junction gaps): table(mcols(first(galp))$NM) table(mcols(last(galp))$NM) table(mcols(first(galp))$NM + mcols(last(galp))$NM) } ## See README.TXT in scripts/ folder: README_file <- system.file("scripts", "README.TXT", package="RNAseqData.HNRNPC.bam.chr14") cat(readLines(README_file), sep="\n")RNAseqData.HNRNPC.bam.chr14_RUNNAMES RNAseqData.HNRNPC.bam.chr14_BAMFILES if (require(GenomicAlignments)) { bamfiles <- RNAseqData.HNRNPC.bam.chr14_BAMFILES param <- ScanBamParam(tag="NM") galp <- readGAlignmentPairs(bamfiles[1L], use.names=TRUE, param=param) galp first(galp) # 1st segment in each pair last(galp) # 2nd segment in each pair ## The alignments contain insertions, deletions, and junctions (I, D, ## and N CIGAR operations, respectively): colSums(cigarOpTable(cigar(first(galp)))) colSums(cigarOpTable(cigar(last(galp)))) ## njunc() returns the nb of junctions for each alignment: table(njunc(first(galp))) table(njunc(last(galp))) table(njunc(first(galp)) + njunc(last(galp))) # up to 5 junctions # per pair! ## The NM tag gives the edit distance of each alignment to the ## reference (ignoring the junction gaps): table(mcols(first(galp))$NM) table(mcols(last(galp))$NM) table(mcols(first(galp))$NM + mcols(last(galp))$NM) } ## See README.TXT in scripts/ folder: README_file <- system.file("scripts", "README.TXT", package="RNAseqData.HNRNPC.bam.chr14") cat(readLines(README_file), sep="\n")