henhaobio
Sign in

BioinformaticsBioinformaticsPeer-reviewed journal article

Snaptron: querying and visualizing splicing across tens of thousands of RNA-seq samples

Christopher WilksiD, Phani Gaddipati, Abhinav NelloreiD, Ben LangmeadiD

PDFDOIPreprintCode
Citations
58
FWCI
1.34
Field percentile
top 20%

Abstract

As more and larger genomics studies appear, there is a growing need for comprehensive and queryable cross-study summaries. Snaptron is a search engine for summarized RNA sequencing data with a query planner that leverages R-tree, B-tree and inverted indexing strategies to rapidly execute queries over 146 million exon-exon splice junctions from over 70,000 human RNA-seq samples. Queries can be tailored by constraining which junctions and samples to consider. Snaptron can also rank and score junctions according to tissue specificity or other criteria. Further, Snaptron can rank and score samples according to the relative frequency of different splicing patterns. We outline biological questions that can be explored with Snaptron queries, including a study of novel exons in annotated genes, of exonization of repetitive element loci, and of a recently discovered alternative transcription start site for the ALK gene. Web app and documentation are at http://snaptron.cs.jhu.edu. Source code is at https://github.com/ChristopherWilks/snaptron under the MIT license.

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISWilks '21Nellore '16Rot '23Sein '19Kahles '16Mapleson '18
72% semantic matchGenomics
Christopher Wilks, Shijie Zheng, Feng Yong Chen+12 more·Genome biology·Nov 29, 2021· 262 citations