sqtlseeker2-nf

sqtlseeker2-nf maps splicing quantitative trait loci (sQTLs) from RNA sequencing data using the R package sQTLseekeR2 to identify genetic variants that influence alternative splicing.

Key Features:

• Multivariate Phenotype Analysis: Represents splicing as the distribution of relative abundances of alternative transcript isoforms to treat splicing as a multivariate phenotype.
• Statistical Framework: Uses a distance-based, non-parametric analogue to multivariate analysis of variance to compute variability in splicing ratios across observations.
• Pipeline Workflow: Performs indexing of the genotype file, preprocessing of transcript expression data, testing for cis associations in a nominal pass, optional permutation testing for empirical P-values, and multiple testing correction.
• Empirical Validation: Has been validated on GTEx and Geuvadis datasets, identifying hundreds of sQTLs including overlaps with genome-wide association study (GWAS) SNPs.

Scientific Applications:

• Discovery of Regulatory Loci: Identifies genetic variants that affect splicing, including variants that alter splice site sequences or modify RNA-binding protein binding sites.
• Insight into Splicing Regulation Mechanisms: Characterizes global splicing patterns and highlights sQTLs in post-transcriptionally spliced introns as regulatory hotspots.
• Phenotypic Impact Analysis: Enables assessment of how variants affecting splicing can exert phenotypic effects that may be more pronounced than those influencing gene expression alone.

Methodology:

Uses sQTLseekeR2 to represent isoform relative abundances, applies a distance-based non-parametric MANOVA-like test, indexes genotype files, preprocesses transcript expression data, performs cis association tests (nominal), optionally computes empirical P-values by permutation, and applies multiple testing correction.