Implement: MAST

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

Usage

methodWrapper.mast(counts, condition, pseudocount = 0.5,
  control = list(save_modelFit = FALSE, include_cdr = TRUE))

methodWrapper.rots(counts, condition, control = list(save_modelFit = FALSE,
  seed = NULL, B = 100))

Arguments

counts	Gene by sample expression count matrix (G by N). MAST requires the default input to be log2CPM. In this function, the required input is normalized expression counts, such as CPM. log2CPM is computed internally.
condition	Binary vector of length N indicating sample biological condition.
pseudocount	Default .5.
control	A list with control arguments, including save_modelFit TRUE to output the complete DESeq2 fit results. include_cdr MAST internal argument. TRUE if include cellular detection rate (fraction of genes detected per sample) as a covariate (scaled to mean 0 and standard deviation 1).
counts	Gene by sample expression count matrix (G by N). ROTS requires this input to be normalized expression matrix, such as FPKM or CPM.
condition	Binary vector of length N indicating sample biological condition.
control	List with control arguments, including save_modelFit TRUE to output the complete DESeq2 fit results. B ROTS internal argument: Number of bootstraps. Default 100. seed ROTS internal argument: An integer seed for the random number generator. Default NULL.

Value

List with the following objects betahat The estimate effect size of condition for all genes. sebetahat The standard errors of the effect sizes. df The degrees of freedom associated with the effect sizes. pvalue P-values of the effect sizes from the likelihood ratio test of the hurdle model, which combines the continous and the discrete component (the above betahat, sebetahat, and df are extracted from the continuous component.) fit MAST complete output of the model fit.

A list with the following objects sig_order Z-socres of expression difference, ordered from the most significant to the least significant. fit ROTS complete output of the model fit.

Functions

• methodWrapper.mast: MAST.

• methodWrapper.rots: ROTS 1.2.0.

Author(s)

Chiaowen Joyce Hsiao

Chiaowen Joyce Hsiao

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