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Joshua Fry

dblp:287/3359 · DBLP profile ↗
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1ranked-venue papers
1as first author
1since 2021 · last 2022
—ORCID · unresolved

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 1 · 1 first-author · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
1 paper
Bioinformatics and computational biology · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › transcriptomics
alternative splicing analysis
0.612022
ScanExitronLR: characterization and quantification of exitron splicing events in long-read RNA-seq data · Bioinform. 2022
Bioinformatics and computational biology › genomics › next-generation sequencing data analysis
long-read sequencing analysis
0.612022
ScanExitronLR: characterization and quantification of exitron splicing events in long-read RNA-seq data · Bioinform. 2022
Bioinformatics and computational biology › transcriptomics
RNA-seq analysis
0.612022
ScanExitronLR: characterization and quantification of exitron splicing events in long-read RNA-seq data · Bioinform. 2022

Methods — techniques the papers use, named apart from their topics

nonsense-mediated decay prediction · 0.6frameshift annotation · 0.6alignment-based detection · 0.6
YearPublicationVenuePosition
2022 ScanExitronLR: characterization and quantification of exitron splicing events in long-read RNA-seq data
abstract
SUMMARY: Exitron splicing is a type of alternative splicing where coding sequences are spliced out. Recently, exitron splicing has been shown to increase proteome plasticity and play a role in cancer. Long-read RNA-seq is well suited for quantification and discovery of alternative splicing events; however, there are currently no tools available for the detection and annotation of exitrons in long-read RNA-seq data. Here, we present ScanExitronLR, an application for the characterization and quantification of exitron splicing events in long-reads. From a BAM alignment file, reference genome and reference gene annotation, ScanExitronLR outputs exitron events at the individual transcript level. Outputs of ScanExitronLR can be used in downstream analyses of differential exitron splicing. In addition, ScanExitronLR optionally reports exitron annotations such as truncation or frameshift type, nonsense-mediated decay status and Pfam domain interruptions. We demonstrate that ScanExitronLR performs better on noisy long-reads than currently published exitron detection algorithms designed for short-read data. AVAILABILITY AND IMPLEMENTATION: ScanExitronLR is freely available at https://github.com/ylab-hi/ScanExitronLR and distributed as a pip package on the Python Package Index. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Joshua Fry, Rendong Yang
Bioinform.1