rliger: getFactorMarkers – R documentation

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getFactorMarkers

Find shared and dataset-specific markers

Description

Applies various filters to genes on the shared (W) and dataset-specific (V) components of the factorization, before selecting those which load most significantly on each factor (in a shared or dataset-specific way).

Usage

getFactorMarkers(
  object,
  dataset1 = NULL,
  dataset2 = NULL,
  factor.share.thresh = 10,
  dataset.specificity = NULL,
  log.fc.thresh = 1,
  pval.thresh = 0.05,
  num.genes = 30,
  print.genes = FALSE,
  verbose = TRUE
)

Arguments

`object`	`liger` object. Should call optimizeALS before calling.
`dataset1`	Name of first dataset (default first dataset by order)
`dataset2`	Name of second dataset (default second dataset by order)
`factor.share.thresh`	Use only factors with a dataset specificity less than or equalt to threshold (default 10).
`dataset.specificity`	Pre-calculated dataset specificity if available. Will calculate if not available.
`log.fc.thresh`	Lower log-fold change threshold for differential expression in markers (default 1).
`pval.thresh`	Upper p-value threshold for Wilcoxon rank test for gene expression (default 0.05).
`num.genes`	Max number of genes to report for each dataset (default 30).
`print.genes`	Print ordered markers passing logfc, umi and frac thresholds (default FALSE).
`verbose`	Print messages (TRUE by default)

Value

List of shared and specific factors. First three elements are dataframes of dataset1- specific, shared, and dataset2-specific markers. Last two elements are tables indicating the number of factors in which marker appears.

Examples

## Not run: 
# ligerex (liger object), factorization complete input
markers <- getFactorMarkers(ligerex, num.genes = 10)
# look at shared markers
head(markers[[2]])

## End(Not run)

rliger

Linked Inference of Genomic Experimental Relationships

v1.0.0

GPL-3

Authors

Joshua Welch [aut, ctb], Chao Gao [aut, ctb, cre], Jialin Liu [aut, ctb], Joshua Sodicoff [aut, ctb], Velina Kozareva [aut, ctb], Evan Macosko [aut, ctb], Paul Hoffman [ctb], Ilya Korsunsky [ctb], Robert Lee [ctb]

Initial release

2021-04-18