Published October 29, 2020 | Version v6
Dataset Open

The impact of biological sex on alternative splicing

Description

These files were pulled from the results obtained through the execution of the Nextflow workflow rmats-nf and through numerous notebooks. How the data were generated are noted for each file.

  1. fromGTF.tar.gz - One for each splicing type, generated within rmats-nf: fromGTF.A3SS.txt, fromGTF.A5SS.txt, fromGTF.MXE.txt, fromGTF.RI.txt,fromGTF.SE.txt.
  2. gtex.tar.gz.  This is a a tar'd and gzipped version of the corrected gtex.corrected.rds file that is constructed by the `differentialGeneExpressionAnalysis.ipynb` jupyter notebook.  A cautionary note, the latest version of GTEx is through AnViL -- see note regarding latest access ability to (GTEx data)[GTEx.md].
  3. rmats_final.tar.gz.   For each splicing type, we have 5 files for there is a matrix of all included junction (ijc) counts, inclusion lengths (inclen), percent spliced in as calculated by rMATS 3.2.5, skipped junction counts (sjc) and skipped junction lengths (skiplen) for each junction and for each sample (SRR) generated by rmats-nf.
  4. SraRunTable.txt.gz.  Old way of obtaining GTEx accessions.
  5. srr.tar.gz - This file contains the Sequence Run (SRR) data merged with phenotype data, generated by differentialGeneExpressionAnalysis.ipynb

Notes

https://github.com/lifebit-ai/rmats-nf was run on Genotype-Tissue Expression (GTEx) RNAseq data (an application to dbGAP for access to the dataset phs000424.v8.v2 is required). This raw data is under controlled access and subject to the data use agreement thereunder. Public posting of Genomic Summary Results is permitted. We post here in this release, genomic summary results from our analysis using rMATS 3.2.5 in the aforementioned nextflow script. We acknowledge the Genotype Tissue Expression (GTEx) Project. The Genotype-Tissue Expression (GTEx) Project was supported by the Common Fund of the Office of the Director of the National Institutes of Health (commonfund.nih.gov/GTEx). Additional funds were provided by the NCI, NHGRI, NHLBI, NIDA, NIMH, and NINDS. Donors were enrolled at Biospecimen Source Sites funded by NCI\Leidos Biomedical Research, Inc. subcontracts to the National Disease Research Interchange (10XS170), Roswell Park Cancer Institute (10XS171), and Science Care, Inc. (X10S172). The Laboratory, Data Analysis, and Coordinating Center (LDACC) was funded through a contract (HHSN268201000029C) to the The Broad Institute, Inc. Biorepository operations were funded through a Leidos Biomedical Research, Inc. subcontract to Van Andel Research Institute (10ST1035). Additional data repository and project management were provided by Leidos Biomedical Research, Inc.(HHSN261200800001E). The Brain Bank was supported supplements to University of Miami grant DA006227. Statistical Methods development grants were made to the University of Geneva (MH090941 & MH101814), the University of Chicago (MH090951,MH090937, MH101825, & MH101820), the University of North Carolina - Chapel Hill (MH090936), North Carolina State University (MH101819),Harvard University (MH090948), Stanford University (MH101782), Washington University (MH101810), and to the University of Pennsylvania (MH101822). The datasets used for the analyses described in this manuscript were obtained from dbGaP at http://www.ncbi.nlm.nih.gov/gap through dbGaP accession number phs000424.v8.v2.

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