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Sidney Cadot

dblp:64/2446 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2012
—ORCID · none

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

Applied, interdisciplinary, general and emerging computing · 1

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 · 67% Computational science and engineering · 33%

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

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology
cancer genomics
0.112012
A regression model for estimating DNA copy number applied to capture sequencing data · Bioinform. 2012
Bioinformatics and computational biology › cancer genomics › copy number analysis
copy number alteration detection
0.112012
A regression model for estimating DNA copy number applied to capture sequencing data · Bioinform. 2012
Computational science and engineering
regression modeling
0.112012
A regression model for estimating DNA copy number applied to capture sequencing data · Bioinform. 2012

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

linear regression · 0.1capture sequencing · 0.1
YearPublicationVenuePosition
2012 A regression model for estimating DNA copy number applied to capture sequencing data
abstract
MOTIVATION: Target enrichment, also referred to as DNA capture, provides an effective way to focus sequencing efforts on a genomic region of interest. Capture data are typically used to detect single-nucleotide variants. It can also be used to detect copy number alterations, which is particularly useful in the context of cancer, where such changes occur frequently. In copy number analysis, it is a common practice to determine log-ratios between test and control samples, but this approach results in a loss of information as it disregards the total coverage or intensity at a locus. RESULTS: We modeled the coverage or intensity of the test sample as a linear function of the control sample. This regression approach is able to deal with regions that are completely deleted, which are problematic for methods that use log-ratios. To demonstrate the utility of our approach, we used capture data to determine copy number for a set of 600 genes in a panel of nine breast cancer cell lines. We found high concordance between our results and those generated using a single-nucleotide polymorphsim genotyping platform. When we compared our results with other log-ratio-based methods, including ExomeCNV, we found that our approach produced better overall correlation with SNP data. AVAILABILITY: The algorithm is implemented in C and R and the code can be downloaded from http://bioinformatics.nki.nl/ocs/ CONTACT: [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Guillem Rigaill, Sidney Cadot, Roelof J. C. Kluin, Zheng Xue, René Bernards, Ian J. Majewski, Lodewyk F. A. Wessels
Bioinform.2