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Samuel O'donnell

dblp:276/0554 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 2020
0000-0003-2447-1993ORCID · reported

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

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

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
genomics
0.412020
MUM&Co: accurate detection of all SV types through whole-genome alignment · Bioinform. 2020
Bioinformatics and computational biology › comparative genomics › genome rearrangement
inversion detection
0.412020
MUM&Co: accurate detection of all SV types through whole-genome alignment · Bioinform. 2020
Bioinformatics and computational biology › genomics › structural variation
structural variation detection
0.412020
MUM&Co: accurate detection of all SV types through whole-genome alignment · Bioinform. 2020

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

whole-genome alignment · 0.4nucmer · 0.4
YearPublicationVenuePosition
2020 MUM&Co: accurate detection of all SV types through whole-genome alignment
abstract
SUMMARY: MUM&Co is a single bash script to detect structural variations (SVs) utilizing whole-genome alignment (WGA). Using MUMmer's nucmer alignment, MUM&Co can detect insertions, deletions, tandem duplications, inversions and translocations greater than 50 bp. Its versatility depends upon the WGA and therefore benefits from contiguous de-novo assemblies generated by third generation sequencing technologies. Benchmarked against five WGA SV-calling tools, MUM&Co outperforms all tools on simulated SVs in yeast, plant and human genomes and performs similarly in two real human datasets. Additionally, MUM&Co is particularly unique in its ability to find inversions in both simulated and real datasets. Lastly, MUM&Co's primary output is an intuitive tabulated file containing a list of SVs with only necessary genomic details. AVAILABILITY AND IMPLEMENTATION: https://github.com/SAMtoBAM/MUMandCo. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Samuel O'donnell, Gilles Fischer
Bioinform.1