MntJULiP and Jutils: Differential splicing analysis of RNA-seq data with covariates.

ABSTRACT: Differences in alternative splicing patterns can reveal important markers of phenotypic differentiation, including biomarkers of disease. Emerging large and complex RNA-seq datasets from disease and population studies include multiple confounders such as sex, age, ethnicity and clinical attributes, which demand highly specialized data analysis tools. However, few methods are equipped to handle the new challenges. We describe an implementation of our programs MntJULiP and Jutils for differential splicing detection and visualization from RNA-seq data that takes into account covariates. MntJULiP detects intron-level differences in alternative splicing from RNA-seq data using a Bayesian mixture model. Jutils visualizes alternative splicing variation with heatmaps, PCA and sashimi plots, and Ve

SUBMITTER: Lui WW 

PROVIDER: S-EPMC10802308 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature