gficf: Gene Frequency - Inverse Cell Frequency (GF-ICF)

In dibbelab/gficf: Gene Frequency - Inverse Cell Frequency

Gene Frequency - Inverse Cell Frequency (GF-ICF)

Description

R implementation of the GF-ICF (https://www.frontiersin.org/articles/10.3389/fgene.2019.00734/abstract) Thanks to 3’-end scRNA-seq approaches, we can now have an accurate estimation of gene expression without having to account for gene length, thus the number of transcripts (i.e. UMI) associated to each gene, strictly reflects the frequency of a gene in a cell, exactly like a word in a document. GFICF (Gene Frequency - Inverce Cell Frequency) is analugous of TF-IDF scoring method as defined for tex dada. With GFICF we consider a cell to be analogous to a document, genes analogous to words and gene counts to be analogous of the word’s occurrence in a document.

Usage

gficf(
  M,
  cell_proportion_max = 1,
  cell_proportion_min = 0.05,
  storeRaw = TRUE,
  normalize = TRUE,
  verbose = TRUE
)

Arguments

M	Matrix; UMI cell count matrix
cell_proportion_max	integer; Remove genes present in more then to the specifided proportion (0,1). Default 1.
cell_proportion_min	integer; Remove genes present in less then or equal to the specifided proportion (0,1). Default is 0.05 (i.e. 5 percent).
storeRaw	logical; Store UMI counts.
normalize	logical; Rescale UMI counts before applay GFICF. Recaling is done using EdgeR normalization.
verbose	boolean; Increase verbosity.

Value

The updated gficf object.

dibbelab/gficf documentation built on Nov. 2, 2022, 2:28 a.m.