simulate_experiment_countmat {polyester} | R Documentation

## Simulate RNA-seq experiment

### Description

create FASTA files containing RNA-seq reads simulated from provided transcripts, with optional differential expression between two groups (designated via read count matrix)

### Usage

    simulate_experiment_countmat(fasta = NULL, gtf = NULL, seqpath = NULL,
      readmat, outdir = ".", paired = TRUE, seed = NULL, ...)

### Arguments

`fasta` | path to FASTA file containing transcripts from which to simulate reads. See details.
`gtf` | path to GTF file or data frame containing transcript structures from which reads should be simulated. See details and `seq_gtf`.
`seqpath` | path to folder containing one FASTA file (`.fa` extension) or DNAStringSet containing one entry for each chromosome in `gtf`. See details and `seq_gtf`.
`readmat` | matrix with rows representing transcripts and columns representing samples. Entry i,j specifies how many reads to simulate from transcript i for sample j.
`outdir` | character, path to folder where simulated reads should be written, without a slash at the end of the folder name. By default, reads written to the working directory.
`paired` | If `TRUE`, paired-end reads are simulated; else single-end reads are simulated.
`seed` | Optional seed to set before simulating reads, for reproducibility.
`...` | Additional arguments to add nuance to the simulation, as described extensively in the details of `simulate_experiment`, or to pass to `seq_gtf`, if `gtf` is not `NULL`.

### Details

Reads can either be simulated from a FASTA file of transcripts (provided with the `fasta` argument) or from a GTF file plus DNA sequences (provided with the `gtf` and `seqpath` arguments). Simulating from a GTF file and DNA sequences may be a bit slower: it took about 6 minutes to parse the GTF/sequence files for chromosomes 1-22, X, and Y in hg19.

### Value

No return, but simulated reads are written to `outdir`.

### References

Li W and Jiang T (2012): Transcriptome assembly and isoform expression level estimation from biased RNA-Seq reads. Bioinformatics 28(22): 2914-2921.

### Examples

      fastapath = system.file("extdata", "chr22.fa", package="polyester")
      numtx = count_transcripts(fastapath)
      readmat = matrix(20, ncol=10, nrow=numtx)
      readmat[1:30, 1:5] = 40

      simulate_experiment_countmat(fasta=fastapath,
        readmat=readmat, outdir='simulated_reads_2', seed=5)

[Package polyester version 1.28.0 Index]