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Richard W. Tothill

dblp:16/11329 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 2014
0000-0003-4522-1184ORCID · corroborated

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

Applied, interdisciplinary, general and emerging computing · 2

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
2 papers
Bioinformatics and computational biology · 100%

Topics — the 7 heaviest of 7, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology
cancer genomics
0.212014
Socrates: identification of genomic rearrangements in tumour genomes by re-aligning soft clipped reads · Bioinform. 2014
Bioinformatics and computational biology › genomics › structural variation
genomic rearrangement detection
0.212014
Socrates: identification of genomic rearrangements in tumour genomes by re-aligning soft clipped reads · Bioinform. 2014
Bioinformatics and computational biology › genomics › structural variation
structural variant detection
0.212014
Socrates: identification of genomic rearrangements in tumour genomes by re-aligning soft clipped reads · Bioinform. 2014
Bioinformatics and computational biology › cancer genomics › copy number analysis
copy number variation detection
0.112012
CONTRA: copy number analysis for targeted resequencing · Bioinform. 2012
Bioinformatics and computational biology › genomics
genomic variant analysis
0.112012
CONTRA: copy number analysis for targeted resequencing · Bioinform. 2012
Bioinformatics and computational biology › genomics › high-throughput sequencing
targeted resequencing
0.112012
CONTRA: copy number analysis for targeted resequencing · Bioinform. 2012
Bioinformatics and computational biology › sequence analysis
sequencing data analysis
0.012012
CONTRA: copy number analysis for targeted resequencing · Bioinform. 2012

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

split-read alignment · 0.2soft-clip re-alignment · 0.2parallel computing · 0.2binning and interpolation · 0.1GC-content bias correction · 0.1
YearPublicationVenuePosition
2014 Socrates: identification of genomic rearrangements in tumour genomes by re-aligning soft clipped reads
abstract
MOTIVATION: Methods for detecting somatic genome rearrangements in tumours using next-generation sequencing are vital in cancer genomics. Available algorithms use one or more sources of evidence, such as read depth, paired-end reads or split reads to predict structural variants. However, the problem remains challenging due to the significant computational burden and high false-positive or false-negative rates. RESULTS: In this article, we present Socrates (SOft Clip re-alignment To idEntify Structural variants), a highly efficient and effective method for detecting genomic rearrangements in tumours that uses only split-read data. Socrates has single-nucleotide resolution, identifies micro-homologies and untemplated sequence at break points, has high sensitivity and high specificity and takes advantage of parallelism for efficient use of resources. We demonstrate using simulated and real data that Socrates performs well compared with a number of existing structural variant detection tools. AVAILABILITY AND IMPLEMENTATION: Socrates is released as open source and available from http://bioinf.wehi.edu.au/socrates CONTACT: [email protected] Supplementary information: Supplementary data are available at Bioinformatics online.
Jan Schröder, Arthur L. Hsu, Samantha E. Boyle, Geoff MacIntyre, Marek Cmero, Richard W. Tothill, Ricky W. Johnstone, Mark Shackleton, Anthony T. Papenfuss
Bioinform.6
2012 CONTRA: copy number analysis for targeted resequencing
abstract
Abstract Motivation: In light of the increasing adoption of targeted resequencing (TR) as a cost-effective strategy to identify disease-causing variants, a robust method for copy number variation (CNV) analysis is needed to maximize the value of this promising technology. Results: We present a method for CNV detection for TR data, including whole-exome capture data. Our method calls copy number gains and losses for each target region based on normalized depth of coverage. Our key strategies include the use of base-level log-ratios to remove GC-content bias, correction for an imbalanced library size effect on log-ratios, and the estimation of log-ratio variations via binning and interpolation. Our methods are made available via CONTRA (COpy Number Targeted Resequencing Analysis), a software package that takes standard alignment formats (BAM/SAM) and outputs in variant call format (VCF4.0), for easy integration with other next-generation sequencing analysis packages. We assessed our methods using samples from seven different target enrichment assays, and evaluated our results using simulated data and real germline data with known CNV genotypes. Availability and implementation: Source code and sample data are freely available under GNU license (GPLv3) at http://contra-cnv.sourceforge.net/ Contact: [email protected] Supplementary information: Supplementary data are available at Bioinformatics online.
Jason Li 0002, Richard Lupat, Kaushalya C. Amarasinghe, Ella R. Thompson, Maria A. Doyle, Georgina L. Ryland, Richard W. Tothill, Saman K. Halgamuge, Ian G. Campbell, Kylie L. Gorringe
Bioinform.7