iPrnaseq: Intron Pointer

In harshsharma-cb/FASE: Analysis of RNA-Sequencing data using FASE (Finding Alternative Splicing Events).

Intron Pointer

Description

Prediction of intron retention events by utilizing information of meta-features (flanking junctions, skipping junctions and introns) associated with the intron in context for a given gene.

Usage

iPrnaseq(
  Gcount,
  iMM,
  designM,
  contrastM,
  Groups = NULL,
  p = 1,
  threshold = 3,
  annotation = annotation,
  ...
)

Arguments

Gcount	list; contains gene-wise matrix of meta-features read counts times samples, generated by countMatrixGenes.
iMM	gene-wise list that represents the association of intron with other meta-features of genes (exons and junctions (skipping/flanking)). It is generated using intronMembershipMatrix.
designM	design matrix required by limma.
contrastM	contrast matrix required by limma.
Groups	list of sample groups. Example: If there are two sample groups with three samples each, 'Groups' should be formed as: numeric: c(1, 1, 1, 2, 2, 2) alphabetical: c('A', 'A', 'A', 'B', 'B', 'B')
p	number of threads to be used if running in parallel. (default=1)
threshold	minimum number of reads that should map to a meta-feature (default=3). If number of reads<threshold, meta-feature would be discarded.
annotation	matrix; contains annotation of exons and introns, created using readMembershipMatrix.
...	other parameters to be passed to eBayes, voom, calcNormFactors and lmFit .

Details

IntronPointer algorithm finds intron retention events using metafeatures (exons, introns and junctions). The read counts of meta-features are present in Gcount and the association of an intron with exons and junctions is given by Intron Membership Matrix (iMM).
In order to find an intron retention event, one-tailed p-values of metafeatures are summarized using Irwin-Hall method to find the equivalent P-value (EqP). EqP determines if an event is differentially alternatively spliced.For more details, please refer: S. S. Tabrez, R. D. Sharma, V. Jain, A. A. Siddiqui & A. Mukhopadhyay. Differential alternative splicing coupled to nonsense-mediated decay of mRNA ensures dietary restriction-induced longevity. Nature Communications volume 8, Article number: 306 (2017).

Value

IntronPointer gives a list of ranked intron retention events with equivalent p-value and t-statistics. The output of iPrnaseq can be passed to addAnnotationRnaSeq to add annotation to the ranked intron retention events.

References

1. S. S. Tabrez, R. D. Sharma, V. Jain, A. A. Siddiqui & A. Mukhopadhyay. Differential alternative splicing coupled to nonsense-mediated decay of mRNA ensures dietary restriction-induced longevity. Nature Communications volume 8, Article number: 306 (2017).

2. Robinson, M. D., McCarthy, D. J. & Smyth, G. K. edgeR: A Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics 26, 139–140 (2009).

3. Ritchie, M. E., Phipson, B., Wu, D., Hu, Y., Law, C. W., Shi, W., & Smyth, G. K. limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic acids research, 43(7), e47 (2015).

4. Henrik Bengtsson (2017). matrixStats: Functions that Apply to Rows and Columns of Matrices (and to Vectors). R package version 0.52.2. https://github.com/HenrikBengtsson/matrixStats

5. https://git.bioconductor.org/packages/Biobase

6. Huber W, Carey VJ, Gentleman R, Anders S, Carlson M, Carvalho BS, Bravo HC, Davis S, Gatto L, Girke T, Gottardo R, Hahne F, Hansen KD, Irizarry RA, Lawrence M, Love MI, MacDonald J, Obenchain V, Ole's AK, Pag'es H, Reyes A, Shannon P, Smyth GK, Tenenbaum D, Waldron L, Morgan M (2015). “Orchestrating high-throughput genomic analysis with Bioconductor.” Nature Methods, 12(2), 115–121.

7. https://CRAN.R-project.org/view=HighPerformanceComputing

harshsharma-cb/FASE documentation built on Aug. 6, 2023, 1:37 a.m.