ccr.get.nonExpGenes: Non expressed genes in a given cell line

In francescojm/CRISPRcleanR: Unsupervised correction of gene independent cell responses to CRISPR-cas9 targeting

Non expressed genes in a given cell line

Description

This function takes in input the name (or the COSMIC identifier [1]) of a cell line and it identifies genes that are not expressed (according to a user defined FPKM threshold) using a collection of RNAseq profile from [2].

Usage

ccr.get.nonExpGenes(cellLine, th = 0.05,
                    amplified = FALSE, minCN = 8,
                    RNAseq.fpkms=NULL,GDSC.CL_annotation=NULL)

Arguments

cellLine	A string specifying the name of a cell line (or a COSMIC identifier [1]);
th	Minimum FPKM value for a gene to be considered as expressed;
amplified	A logic value specifying whether the selected not expressed genes should be also copy number amplified function;
minCN	If amplified = TRUE, this parameter defines a lower threshold for the minimum copy number of any genomic segment containing coding sequence of a gene in order for it to be considered as copy number amplified.
RNAseq.fpkms	Genome-wide substitute reads with fragments per kilobase of exon per million reads mapped (FPKM) across cell lines. These can be derived from a comprehensive collection of RNAseq profiles described in [2]. The format must be the same of the RNAseq.fpkms builtin data frame. If NULL then this function uses the RNAseq.fpkms builtin data fram containing data for 15 cell lines used in [3] to assess CRISPRcleaneR results.
GDSC.CL_annotation	Cell lines annotation dataframe with the same structure of the GDSC.CL_annotation. If NULL then the GDSC.CL_annotation is used.

Value

A vector of string containing the HGNC symbols of non expressed (optionally copy number amplified) genes in the cell line under consideration.

Author(s)

Francesco Iorio ([e-mail])

References

[1] Forbes SA, Beare D, Boutselakis H, et al. COSMIC: somatic cancer genetics at high-resolution Nucleic Acids Research, Volume 45, Issue D1, 4 January 2017, Pages D777-D783.

[2] Garcia-Alonso L, Iorio F, Matchan A, et al. Transcription factor activities enhance markers of drug response in cancer doi: https://doi.org/10.1101/129478

[3] Iorio, F., Behan, F. M., Goncalves, E., Beaver, C., Ansari, R., Pooley, R., et al.
Unsupervised correction of gene-independent cell responses to CRISPR-Cas9 targeting.
http://doi.org/10.1101/228189

See Also

ccr.get.gdsc1000.AMPgenes

Examples

    ccr.get.nonExpGenes('HT-29',amplified = TRUE)

francescojm/CRISPRcleanR documentation built on April 30, 2023, 5:41 a.m.