EventPointer 3.0: flexible and accurate splicing analysis that includes studying the differential usage of protein-domains

Abstract

Alternative splicing (AS) plays a key role in cancer: all its hallmarks have been associated with different mechanisms of abnormal AS. The improvement of the human transcriptome annotation and the availability of fast and accurate software to estimate isoform concentrations has boosted the analysis of transcriptome profiling from RNA-seq. The statistical analysis of AS is a challenging problem not yet fully solved. We have included in EventPointer (EP), a Bioconductor package, a novel statistical method that can use the bootstrap of the pseudoaligners. We compared it with other state-of-the-art algorithms to analyze AS. Its performance is outstanding for shallow sequencing conditions. The statistical framework is very flexible since it is based on design and contrast matrices. EP now includes a convenient tool to find the primers to validate the discoveries using PCR. We also added a statistical module to study alteration in protein domain related to AS. Applying it to 9514 patients from TCGA and TARGET in 19 different tumor types resulted in two conclusions: i) aberrant alternative splicing alters the relative presence of Protein domains and, ii) the number of enriched domains is strongly correlated with the age of the patients.

ASTK: A Machine Learning‐Based Integrative Software for Alternative Splicing Analysis

“…Our endeavor through this study was to craft an exhaustive pipeline to unravel the functional and regulatory facets of AS. While several computational tools have emerged to quantify transcript isoforms and identify splicing events, [3][4][5][6][7][8][9]12] the functional elucidation of AS events remains an intricate challenge. Traditional gene-level enrichment analyses like GO, KEGG, and GSEA primarily target differential AS genes, often overlooking the fact that a single gene can harbor multiple AS events and exhibit diverse splicing patterns.…”

“…[1] While AS is critical for normal physiological functions, aberrations in this process can lead to a spectrum of diseases. [2] Numerous software tools have been crafted to aid AS research, ranging from the detection and quantification of AS events [3][4][5][6][7][8][9] to time series and isoform switch analysis, [10,11] functional enrichment, [12,13] mapping the spatial distribution of RNA-binding proteins (RBPs) binding motifs, [14] sequence feature extractions, [15,16] and assessing the functional implications of AS changes. [16] Historically, AS studies have been focusing on two main aspects: functionality and regulation.…”

A Systematic Identification of RBPs Driving Aberrant Splicing in Cancer

“…This integrated database provides genomic loci that were mapped to the corresponding genome (hg38 in our case). In EventPointer (11), the potential splicing events were annotated based on a reference transcriptome (in this one GENCODE24). We compared the RBP binding sites and the potential splicing events.…”

“…We have switched to a bootstrap-based statistic recently implemented in the EventPointer package (Figure 1.2). This statistical approach increases the sensitivity compared to the previous version (11).…”

DeepRBP: A novel deep neural network for inferring splicing regulation

“…Given the requirement of a targeted RBP for conducting a CLIP experiment, several algorithms have been developed to predict the potential involvement of specific RBPs in splicing interactions, as they could be used as a new therapeutic targets to treat diseases (Hong, 2017;Li et al, 2021;Carazo et al, 2019;Park et al, 2016;Chen and Keleş, 2020). These methods integrate RBP databases, such as POSTAR3 (Zhao et al, 2022), and a statistical analysis of AS performed by methods such as EventPointer (Ferrer-Bonsoms et al, 2022), rMATS (Shen et al, 2014) or SUPPA (Sebestyén et al, 2016). However, these algorithms are restricted by the number of RBPs available in the CLIP experiment databases.…”