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calculate_gs_scores.Rd
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% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/calculate_gs_scores.R
\name{calculate_gs_scores}
\alias{calculate_gs_scores}
\title{Calculate gene set scores}
\usage{
calculate_gs_scores(
scMuffinList = NULL,
gs_list = NULL,
mc.cores = 1,
nbins = 25,
nmark_min = 5,
ncells_min = 10,
k = 100,
kmin = 50,
score_type = c("relative", "mean"),
verbose = FALSE,
na.rm = TRUE,
overwrite = FALSE
)
}
\arguments{
\item{scMuffinList}{scMuffinList object}
\item{gs_list}{list of gene sets}
\item{mc.cores}{number of cores}
\item{nbins}{number of bins to split the distribution of average gene expression}
\item{nmark_min}{number of minimum markers that are required for the succesful calculation of a gene set score}
\item{ncells_min}{number of minimum cells in which a gene set has to be succesfully calculated}
\item{k}{number of permutations}
\item{kmin}{minimum number of permutations; due to missing values it is hard to ensure that a gene set score can be compared to k permutations in every cell}
\item{score_type}{type of score. if "relative", than the score is the difference between the observed gene set average expression and that of a k permutations; if "mean" the score is equal to the observed gene set average expression}
\item{verbose}{verbosity}
\item{na.rm}{whether to use NA or not}
\item{overwrite}{whether to update or not gene_set_scoring and gene_set_scoring_full elements of scMuffinList.}
}
\value{
scMuffinList with element gene_set_scoring, a list that contains summary and full. The element summary contains a cells-by-gene sets data.frame. The element "full" contains a data.frame for each gene set. See [gs_score()] for further details.
}
\description{
Calculate gene set scores using the approach described in Tirosh2016
}
\references{
Tirosh2016 10.1126/science.aad0501
}