simulate_dropseq_experiment: Simulator: simulate_dropseq_experiment Simulate Dropseq...
In Helena-L/DropseqSimulator: Dropseq Simulator

View source: R/simulate_dropseq_experiment.R

create FASTA files containing RNA-seq reads simulated from provided transcripts, given gene number and cell number

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simulate_dropseq_experiment(fasta = NULL, ngenes = NULL,
  ncells = NULL, libloc = 5, libscale = 0.2, polyAnum = 15,
  bias = "empirical", model = NULL, outdir = ".")

`fasta`	path to FASTA file containing transcripts from which to simulate reads.
`ngenes`	number of genes to simulate
`ncells`	number of cells to simulate
`libloc`	location parameter for the library size log-normal distribution, together with `libscale` controls library size. Determine different sequencing depth (number of reads) between cells.
`libscale`	scale parameter for the library size log-normal distribution, together with `libloc` controls library size. Determine different sequencing depth (number of reads) between ceels.
`polyAnum`	minimum number of 'A's in a polyA region, integer. A region should contain at least n continous 'A's to be considered as a polyA region.
`bias`	polyA sampling bias, one of 'empirical', 'custom' (default 'empirical'). If 'empirical', the built-in model is adopted. This model is trained on data sets from the Drop-seq experiments described in the Cell paper (Macosko et al, 2015). If 'custom', polyA sampling bias is captured from user input model. The path of user input model is specified in `model`.
`model`	path to polyA sampling bias model if `bias` set to 'custom'. Model format should be a data frame with 2 columns. Column 1 is distance to polyA region, while Column 2 is probability of getting a fragment at that position. Column 2 sums to 1.
`outdir`	path to folder where simulated reads should be written. By default, reads written to the working directory.