This repository contains archived versions of the software, and supporting data for the article "MntJULiP and Jutils: Differential splicing analysis of RNA-seq data with covariates"Content:Software (archived versions): MntJULiP-master-covariate.tar.gz (v.1.5.1), Jutils-pca.tar.gz (v.1.5)Simulation analysis: Results [165 MB], Input SPLICES [34 MB]Brain analysis: Results of ByAge comparisons [1.5 GB], Results of BySex comparison [254 MB], Lists of genes for the '20s-vs-40s' and 'male-female' functional analyses (Excel)Related BAM file of simulated data are available from Zenodo: DOI 10.5281/zenodo.14984115 . Current versions of the software can be found at https://github.com/splicebox/ .

This repository contains archived versions of the software, and supporting data for the article "MntJULiP and Jutils: Differential splicing analysis of RNA-seq data with covariates"Content:Software (archived versions): MntJULiP-master-covariate.tar.gz (v.1.5.1), Jutils-pca.tar.gz (v.1.5)Simulation analysis: Results [165 MB], Input SPLICES [34 MB]Brain analysis: Results of ByAge comparisons [1.5 GB], Results of BySex comparison [254 MB], Lists of genes for the '20s-vs-40s' and 'male-female' functional analyses (Excel)Related BAM file of simulated data are available from Zenodo: DOI 10.5281/zenodo.14984115 . Current versions of the software can be found at https://github.com/splicebox/ .

The repository includes alignments of simulated RNA-seq data for evaluating differential splicing detection with covariates. Starting from an empirical transcript expression matrix trained on an RNA-seq data set from lung fibroblasts (GenBank A# SRR493366) and using GENCODE v.41 as reference, 11.5 million 100 bp long paired-end reads were generated per sample, from 2,000 genes with two or more expressed isoforms. RNA-seq data was simulated for one ‘condition’, with values ‘control’, ‘disease’ and ‘stage2’, with one covariate, ‘biological sex’, with values ‘M’ and ‘F’.  10 samples each were simulated for each (condition x sex) category. Changes were simulated in the expression (DE) and/or the splicing ratio (DS) of genes as follows. Changes in expression (DE) were simulated by either halving or doubling the expression level of the gene. Changes in splicing ratios (DS) were simulated by swapping the expression levels of the gene’s top two transcript isoforms. All RNA-seq data was mapped to the hg38 genome with the spliced alignment tool STAR v2.7.10a. Pairwise comparison alignment set: Differences due to ‘condition’ between two states, ‘control’ and ‘disease’, were simulated at 600 genes, including 200 DE, 200 DS and 200 DE+DS genes. Differences in ‘biological sex’ (covariate) were represented as changes in 300 genes, with 100 genes from each of the DS, DE and DE+DS categories. Hence, the target gene set for differential splicing ratio (DSR) pairwise comparisons consists of the pooled 200 DS and 200 DS+DE genes differentially spliced between the ‘control’ and ‘disease’ states, while for differential splicing abundance (DSA) pairwise comparisons the target gene set is the set of 600 modified genes, 200 in each of the DS, DE and DS+DE categories. Multiway (3-way) comparison alignment set: To create the 'stage2' data, changes in expression and splicing levels were maintained for 3 x 100 of the 'disease' genes (100 in each category). Further, 'stage2'-specific changes were made to a set of 200 additional genes not encountered previously, for each of the categories DE, DS and DE+DS. Therefore, for DSR three-way comparisons, the target gene set represents the 800 genes simulated as being DS or DE+DS between any of the ‘control’, ‘disease’ and ’stage2’ categories, while for the multi-way DSA comparisons the target is the full set of 1,200 genes (400 DE, 400 DS and 400 DE+DS) simulated to have changed between any of the 'control', 'disease’ and ‘stage2’ states. Further details: See the ‘key’ package for the gene lists and sample metadata.

The repository includes alignments of simulated RNA-seq data for evaluating differential splicing detection with covariates. Starting from an empirical transcript expression matrix trained on an RNA-seq data set from lung fibroblasts (GenBank A# SRR493366) and using GENCODE v.41 as reference, 11.5 million 100 bp long paired-end reads were generated per sample, from 2,000 genes with two or more expressed isoforms. RNA-seq data was simulated for one ‘condition’, with values ‘control’, ‘disease’ and ‘stage2’, with one covariate, ‘biological sex’, with values ‘M’ and ‘F’.  10 samples each were simulated for each (condition x sex) category. Changes were simulated in the expression (DE) and/or the splicing ratio (DS) of genes as follows. Changes in expression (DE) were simulated by either halving or doubling the expression level of the gene. Changes in splicing ratios (DS) were simulated by swapping the expression levels of the gene’s top two transcript isoforms. All RNA-seq data was mapped to the hg38 genome with the spliced alignment tool STAR v2.7.10a. Pairwise comparison alignment set: Differences due to ‘condition’ between two states, ‘control’ and ‘disease’, were simulated at 600 genes, including 200 DE, 200 DS and 200 DE+DS genes. Differences in ‘biological sex’ (covariate) were represented as changes in 300 genes, with 100 genes from each of the DS, DE and DE+DS categories. Hence, the target gene set for differential splicing ratio (DSR) pairwise comparisons consists of the pooled 200 DS and 200 DS+DE genes differentially spliced between the ‘control’ and ‘disease’ states, while for differential splicing abundance (DSA) pairwise comparisons the target gene set is the set of 600 modified genes, 200 in each of the DS, DE and DS+DE categories. Multiway (3-way) comparison alignment set: To create the 'stage2' data, changes in expression and splicing levels were maintained for 3 x 100 of the 'disease' genes (100 in each category). Further, 'stage2'-specific changes were made to a set of 200 additional genes not encountered previously, for each of the categories DE, DS and DE+DS. Therefore, for DSR three-way comparisons, the target gene set represents the 800 genes simulated as being DS or DE+DS between any of the ‘control’, ‘disease’ and ’stage2’ categories, while for the multi-way DSA comparisons the target is the full set of 1,200 genes (400 DE, 400 DS and 400 DE+DS) simulated to have changed between any of the 'control', 'disease’ and ‘stage2’ states. Further details: See the ‘key’ package for the gene lists and sample metadata.