amplify_cell: Simulate amplification, library prep, and the sequencing...
In JINJINT/splattermodify: Simple Simulation of Single-cell RNA Sequencing Data

Simulate amplification, library prep, and the sequencing processes. (This function is borrowed from SymSim).

1 2	amplify_cell(true_counts_1cell, rate_2cap, gene_len, amp_bias, rate_2PCR, nPCR1, nPCR2, LinearAmp, LinearAmp_coef, N_molecules_SEQ)

`true_counts_1cell`	the true transcript counts for one cell (one vector)
`rate_2cap`	the capture efficiency for this cell
`gene_len`	gene lengths for the genes/transcripts, sampled from real human transcript length
`amp_bias`	amplification bias for each gene, a vector of length ngenes
`rate_2PCR`	PCR efficiency, usually very high
`nPCR1`	the number of PCR cycles
`nPCR2`	the number of second PCR cycles
`LinearAmp`	if linear amplification is used for pre-amplification step, default is FALSE
`LinearAmp_coef`	the coeficient of linear amplification, that is, how many times each molecule is amplified by
`N_molecules_SEQ`	number of molecules sent for sequencing; sequencing depth

UMI counts

Zhang X, Xu C, Yosef N. Simulating multiple faceted variability in single cell RNA sequencing. Nature communications. 2019 Jun 13;10(1):1-6. https://www.nature.com/articles/s41467-019-10500-w

JINJINT/splattermodify documentation built on May 19, 2021, 4:05 p.m.