FindAllMarkers: FindAllMarkers SJ expression markers for all identity classes...

In tangchao7498/ICAS:

Description

FindAllMarkers SJ expression markers for all identity classes

Finds markers (differentially expressed SJs) for each of the identity classes in a dataset

Usage

FindAllMarkers(object, genes.use = NULL, delta.threshold = 0.1,
  test.use = "tobit", min.pct = 0.1, min.diff.pct = -Inf,
  print.bar = TRUE, only.pos = FALSE, max.cells.per.ident = Inf,
  return.thresh = 0.01, random.seed = 1, maxit = 10,
  confounder = NULL, min.cells.gene = 3, min.cells.group = 3,
  NT = 1, ...)

Arguments

object	ICASDataSet object
genes.use	SJs to test. Default is to use all SJs
delta.threshold	Limit testing to SJs which show, on average, at least delta.threshold between the two groups of samples. Default is 0.1 Increasing delta.threshold speeds up the function, but can miss weaker signals.
test.use	Denotes which test to use. Available options are: "wilcox" : Wilcoxon rank sum test "bimod" : Likelihood-ratio test for SJ expression, (McDavid et al., Bioinformatics, 2013) "roc" : Standard AUC classifier "t" : Student's t-test "WD" : waldtest for binomial glm "tobit" : Tobit-test for differential SJ expression (Trapnell et al., Nature Biotech, 2014) (default) "poisson" : Likelihood ratio test assuming an underlying poisson distribution. Use only for UMI-based datasets "negbinom" : Likelihood ratio test assuming an underlying negative binomial distribution. Use only for UMI-based datasets "MAST" : GLM-framework that treates cellular detection rate as a covariate (Finak et al, Genome Biology, 2015) "Hyper" : DE based on Hypergeometric test "BB" : DE based on a generalized linear models using betabinomial distribution
min.pct	only test SJs that are detected in a minimum fraction of min.pct cells in either of the two populations. Meant to speed up the function by not testing SJs that are very infrequently expressed. Default is 0.1
min.diff.pct	only test SJs that show a minimum difference in the fraction of detection between the two groups. Set to -Inf by default
print.bar	Print a progress bar once expression testing begins (uses pbapply to do this)
only.pos	Only return positive markers (FALSE by default)
max.cells.per.ident	Down sample each identity class to a max number. Default is no downsampling.
return.thresh	Only return markers that have a p-value < return.thresh, or a power > return.thresh (if the test is ROC)
random.seed	Random seed for downsampling
maxit	(Only for test.use is BB) maximum number of (usually Fisher-scoring) iterations allowed. Decreasing maxit speeds up the function, but can weaken statistical reliability.
confounder	(Only for test.use is BB) The confounder to regress out.
min.cells.gene	Minimum number of cells expressing the SJ in at least one of the two groups, currently only used for poisson and negative binomial tests
min.cells.group	Minimum number of cells in one of the groups
NT	cores for parallel (Currently only support roc test)
...	Additional parameters to pass to specific DE functions

Value

Matrix containing a ranked list of putative markers, and associated statistics (p-values, ROC score, etc.)

tangchao7498/ICAS documentation built on Jan. 28, 2021, 3:56 p.m.