Comprehensive Cancer Variant Profiling

CaVEMan (Cancer Variants Through Expectation Maximization: http://cancerit.github.io/CaVEMan/) was used for calling somatic substitutions.
Indels in the tumor and normal genomes were called using a modified Pindel version 2.0. (http://cancerit.github.io/cgpPindel/) on the NCBI37 genome build 49 (link).
Structural variants were discovered using a bespoke algorithm, BRASS (BReakpoint AnalySiS) (https://github.com/cancerit/BRASS) through discordantly mapping paired-end reads. Next, discordantly mapping read pairs that were likely to span breakpoints, as well as a selection of nearby properly-paired reads, were grouped for each region of interest. Using the Velvet de novo assembler50 (link), reads were locally assembled within each of these regions to produce a contiguous consensus sequence of each region. Rearrangements, represented by reads from the rearranged derivative as well as the corresponding non-rearranged allele were instantly recognisable from a particular pattern of five vertices in the de Bruijn graph (a mathematical method used in de novo assembly of (short) read sequences) of component of Velvet. Exact coordinates and features of junction sequence (e.g. microhomology or non-templated sequence) were derived from this, following aligning to the reference genome, as though they were split reads.
Supplementary Table 3 for summary of somatic variants. Annotation was according to ENSEMBL version 58.
Single nucleotide polymorphism (SNP) array hybridization using the Affymetrix SNP6.0 platform was performed according to Affymetrix protocols. Allele-specific copy number analysis of tumors was performed using ASCAT (v2.1.1), to generate integral allele-specific copy number profiles for the tumor cells51 (link) (Supplementary Table 4 and 5). ASCAT was also applied to NGS data directly with highly comparable results.
12.5% of the breast cancers were sampled for validation of substitutions, indels and/or rearrangements in order to make an assessment of the positive predictive value of mutation-calling (Supplementary Table 6).
Further details of these processing steps as well as processing of transcriptomic and miRNA data (Supplementary Table 7 and 8) can be found in Supplementary Methods.

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Nik-Zainal S., Davies H., Staaf J., Ramakrishna M., Glodzik D., Zou X., Martincorena I., Alexandrov L.B., Martin S., Wedge D.C., Van Loo P., Ju Y.S., Smid M., Brinkman A.B., Morganella S., Aure M.R., Lingjærde O.C., Langerød A., Ringnér M., Ahn S.M., Boyault S., Brock J.E., Broeks A., Butler A., Desmedt C., Dirix L., Dronov S., Fatima A., Foekens J.A., Gerstung M., Hooijer G.K., Jang S.J., Jones D.R., Kim H.Y., King T.A., Krishnamurthy S., Lee H.J., Lee J.Y., Li Y., McLaren S., Menzies A., Mustonen V., O’Meara S., Pauporté I., Pivot X., Purdie C.A., Raine K., Ramakrishnan K., Rodríguez-González F.G., Romieu G., Sieuwerts A.M., Simpson P.T., Shepherd R., Stebbings L., Stefansson O.A., Teague J., Tommasi S., Treilleux I., Van den Eynden G.G., Vermeulen P., Vincent-Salomon A., Yates L., Caldas C., van’t Veer L., Tutt A., Knappskog S., Tan B.K., Jonkers J., Borg Å., Ueno N.T., Sotiriou C., Viari A., Futreal P.A., Campbell P.J., Span P.N., Van Laere S., Lakhani S.R., Eyfjord J.E., Thompson A.M., Birney E., Stunnenberg H.G., van de Vijver M.J., Martens J.W., Børresen-Dale A.L., Richardson A.L., Kong G., Thomas G, & Stratton M.R. (2016). Landscape of somatic mutations in 560 breast cancer whole genome sequences. Nature, 534(7605), 47-54.

Publication 2016

Allele Brass Cancer Cancers of the breast Consensus sequence Genome Hybridization Indels Mirna Mutation Rearrangements Single nucleotide polymorphism Somatic Transcriptomic Tumor

Corresponding Organization : Institut national de recherche en informatique et en automatique

Other organizations : Lund University, Erasmus MC Cancer Institute, Erasmus MC, Radboud University Nijmegen, European Bioinformatics Institute, Wellcome Trust, Oslo University Hospital, University of Oslo, Gachon University Gil Medical Center, Centre Léon Bérard, Brigham and Women's Hospital, The Netherlands Cancer Institute, Oncode Institute, Institut Jules Bordet, Université Libre de Bruxelles, University of Antwerp, Dana-Farber Cancer Institute, Academic Medical Center, Asan Medical Center, Hanyang University, Memorial Sloan Kettering Cancer Center, The University of Texas MD Anderson Cancer Center, Institut National du Cancer, Inserm, Centre Hospitalier Universitaire de Besançon, Ninewells Hospital, Institut de Recherche en Cancérologie de Montpellier, University of Queensland, University of Iceland, Istituti di Ricovero e Cura a Carattere Scientifico, Istituto Tumori Bari, Institut Curie, University of Cambridge, Cancer Research UK, King's College London, Breast Cancer Now, University of Bergen, National Cancer Centre Singapore, Radboud University Medical Center

Top 5 similar protocols

Protocol cited in 37 other protocols

Variable analysis

independent variables

CaVEMan (Cancer Variants Through Expectation Maximization)
Modified Pindel version 2.0
BRASS (BReakpoint AnalySiS)

dependent variables

Somatic substitutions
Indels in the tumor and normal genomes
Structural variants

control variables

NCBI37 genome build 49
Affymetrix SNP6.0 platform
ASCAT (v2.1.1) for allele-specific copy number analysis

positive controls

12.5% of the breast cancers were sampled for validation of substitutions, indels and/or rearrangements

negative controls

Not explicitly mentioned

Annotations

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