psichomics: graphical application for alternative splicing quantification and analysis

Abstract

Motivation: Alternative pre-mRNA splicing generates functionally distinct transcripts from the same gene and is involved in the control of multiple cellular processes, with its dysregulation being associated with a variety of pathologies. The advent of next-generation sequencing has enabled global studies of alternative splicing in different physiological and disease contexts. However, current bioinformatics tools for alternative splicing analysis from RNA-seq data are not user-friendly, disregard available exon-exon junction quantification or have limited downstream analysis features. Results: We have developed psichomics, an R package with an intuitive graphical interface for alternative splicing quantification and downstream dimensionality reduction, differential splicing and gene expression and survival analyses based on The Cancer Genome Atlas, the Genotype-Tissue Expression project and user-provided data. These integrative analyses can also incorporate clinical and molecular sample-associated features. We successfully used psichomics to reveal alternative splicing signatures specific to stage I breast cancer and associated novel putative prognostic factors. Availability and implementation: psichomics is publicly available in Bioconductor at https://bioconductor.org/packages/psichomics, along with graphical and command-line interface tutorials based on the presented case study.

ASCOT identifies key regulators of neuronal subtype-specific splicing

“…ASCOT's user interface and associated splicing/expression data sets are openly available at http://ascot.cs.jhu.edu. Although there have been past efforts to summarize public RNA-Seq data 28,29,74 , ASCOT represents the largest effort to date to make alternative splicing and gene expression summaries of diverse data sets available to general researchers. ASCOT also demonstrates the value of using annotation-free methods to summarize publicly archived data.…”

“…Numerous algorithms for alternative splicing analysis have been developed [11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26][27] , including several recent studies that propose useful models for studying complex splicing patterns in RNA-Seq data 11,13,25 . However, there is a need for new methods that can summarize alternative splicing across thousands of public data sets in a unified manner, without relying on prior transcript annotation 28,29 .…”

Mutations primarily alter the inclusion of alternatively spliced exons

“…To estimate the PSI of all exons in all GTEx samples ( GTEx Consortium, 2017 ) from the proportion of reads supporting exon inclusion in the GTEx junction read counts file ( GTEx_Analysis_2016-01-15_v7_STARv2.4.2a_junctions.gct.gz ; available for download at https://www.gtexportal.org/home/datasets ), we used the quantifySplicing function from the Psichomics package in R ( Saraiva-Agostinho and Barbosa-Morais, 2019 ). The minReads argument was set to 10 (such that a splicing event requires at least 10 reads for it to be quantified) and the eventType argument was set to ‘SE’ (instructing the quantifySplicing function to quantify alternative exon events).…”

The RNA‐binding protein MEX3A is a prognostic factor and regulator of resistance to gemcitabine in pancreatic ductal adenocarcinoma

“…S1A). Transcriptomic analysis of PDAC samples that were screened for homogenous cancer cell population [29] using the Psycomics tool [30] indicated that MEX3A, and to a lesser extent SRRM1, were expressed at significantly higher levels in basal-like tumors (Fig. 1D).…”