methodWrapper.bpsc: BPSC

In jhsiao999/ashbun: Methods and evaluation tools for single cell RNA-seq count data

Description

Implement BPSC 0.99.1 (not available via Bioconductor). This method requires that the input data is normalized (counts-per-million or fragments per-kilo-base per million).

Usage

methodWrapper.bpsc(counts, condition, control = list(save_modelFit = FALSE,
  estIntPar = FALSE, useParallel = TRUE))

Arguments

counts	Gene by sample expression count matrix (G by N). BPSC requires this input to be normalized expression matrix, such as FPKM or CPM.
condition	Binary vector of length N indicating sample biological condition. #' @param libsize_factors Numeric vector of scale factors for library sizes. Default NULL multiplies all library sizes by 1.
control	A list with control arguments, including save_modelFit TRUE to output the complete DESeq2 fit results. estIntPar BPSC internal argument (TRUE/FALSE) for using only the expressed genes to compute parameter estimates. useParalle BPSC internal argument (TRUE/FALSE) for using code written for parallel computing.

Value

List with the following objects pvalue significance value for the group effect. fit BPSC complete output of the model fit.

Author(s)

Chiaowen Joyce Hsiao

jhsiao999/ashbun documentation built on May 8, 2019, 11:17 p.m.