spliceGenome: Calculate Genome-wide Splicing Scores

In yuhuihui2011/vasp: Quantification and Visualization of Variations of Splicing in Population

Description

Calculate splicing scores from ballgown objects for all genes.

Usage

spliceGenome(bg, gene.select = "rowQuantiles(x,probs = 0.05)>=1",
            intron.select = "rowQuantiles(x,probs = 0.95)>=5")

Arguments

bg	ballgown object
gene.select	logical expression-like string, indicating genes to select from a matrix of gene-level coverages: NA value keeps all genes. e.g. gene.select = 'rowQuantiles(x,probs = 0.05)>=1' keeps the genes with the read coverage greater than or equal to 1 in at least 95 (0.05 quantile). Used to filter low expressed genes.
intron.select	logical expression-like string, indicating introns to select from a matrix of junction counts: NA value keeps all introns. e.g. intron.select = 'rowQuantiles(x,probs = 0.95)>=5' keeps the introns with the read count greater than or euqal to 5 in at least 5 (0.95 quantile). Used to filter introns with very few junction reads supporting.

Details

score = junction count/gene-level per base read coverage. Row functions for matrices in matrixStats package are useful to select genes and introns.

Value

a list of two elelments: 'score' is matrix of intron splicing scores with intron rows and sample columns and 'intron' is a GRanges object of intron structure. See structure in ballgown package

References

Yu, H., Du, Q., Campbell, M., Yu, B., Walia, H. and Zhang, C. (2021), Genome‐wide discovery of natural variation in pre‐mRNA splicing and prioritising causal alternative splicing to salt stress response in rice. New Phytol. https://doi.org/10.1111/nph.17189

See Also

spliceGene, which calculates splicing scores in one gene.

Examples

data(rice.bg)
rice.bg

splice<-spliceGenome(rice.bg,gene.select=NA,intron.select=NA)
names(splice)

head(splice$score)
splice$intron

yuhuihui2011/vasp documentation built on Jan. 12, 2022, 7:50 a.m.