CalMaTe: a method and software to improve allele-specific copy number of SNP arrays for downstream segmentation

Ortiz-Estévez, María; Aramburu, Ander; Bengtsson, Henrik; Neuvial, Pierre; Rubio, Ángel

doi:10.1093/bioinformatics/bts248

Cited by 19 publications

(16 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…12 We performed allele-specific copy number segmentation in nonpaired samples (only tumor DNA) using the CalMaTe algorithm (v0.11). 13 Statistical analyses. All analyses were performed with R-project (v3.0.2).…”

mentioning

confidence: 99%

Allelic loss of 9p21.3 is a prognostic factor in 1p/19q codeleted anaplastic gliomas

Alentorn¹,

Dehais²,

Ducray³

et al. 2015

Neurology

View full text Add to dashboard Cite

Objectives: We aimed to study the potential clinical relevance of 9p allelic loss, with or without copy number variation, in 1p/19q codeleted anaplastic oligodendroglial tumors (AOTs).Methods: This study enrolled 216 patients with 1p/19q codeleted AOT. The prognostic value of 9p allelic loss was investigated using a French nation-wide prospective registry, POLA (prise en charge des tumeurs oligodendrogliales anaplasiques) and high-density single nucleotide polymorphism arrays. We validated our results using the Repository of Molecular Brain Neoplasia Data (REMBRANDT) dataset. Results:The minimal common region of allelic loss in chromosome arm 9p was 9p21.3. Allelic loss of 9p21.3, detected in 41.7% of tumors, was associated with shorter progression-free and overall survival rates in univariate (p 5 0.008 and p , 0.001, respectively) and multivariate analyses (p 5 0.009 and p 5 0.009, respectively). This finding was validated in the REMBRANDT dataset in univariate and multivariate analysis (p 5 0.01 and p 5 0.01, respectively). 4,5 However, in both studies, the median overall survival (OS) in the 1p/19q codeleted subgroup had a broad range of 95% confidence interval (from 6.4 to more than 12 years in one study and a 5-year OS rate from 60.3% to 86.4% in the other study), 4,5 suggesting that some patients would have a less favorable prognosis. Identification of novel biomarkers in this tumor subgroup would help to better stratify patients with 1p/19q codeleted AOT. Conclusion:Although promising novel somatic mutations in CIC (capicua transcriptional repressor) and FUBP1 (far upstream element binding protein 1) have been identified in 1p/19q codeleted

show abstract

mentioning

confidence: 99%

Allelic loss of 9p21.3 is a prognostic factor in 1p/19q codeleted anaplastic gliomas

Alentorn¹,

Dehais²,

Ducray³

et al. 2015

Neurology

View full text Add to dashboard Cite

show abstract

“…The arrays were preprocessed with the ASCRMAv2 single-array method in the aroma.affymetrix R package [30,31], and further adjusted for SNP-specific allelic crosstalk with CalMaTe [32]. Total (signal A plus signal B) tumor SNP array signals were normalized (divided by) towards total SNP array signals of matched normal samples where available, or otherwise position-specific median total SNP array signals across the normal samples, giving TCNs for all tumors.…”

Section: Methodsmentioning

confidence: 99%

Deciphering clonality in aneuploid breast tumors using SNP array and sequencing data

Lönnstedt

Caramia

et al. 2014

Genome Biol

View full text Add to dashboard Cite

Intra-tumor heterogeneity concerns the existence of genetically different subclones within the same tumor. Single sample quantification of heterogeneity relies on precise determination of chromosomal copy numbers throughout the genome, and an assessment of whether identified mutation variant allele fractions match clonal or subclonal copy numbers. We discuss these issues using data from SNP arrays, whole exome sequencing and pathologist purity estimates on several breast cancers characterized by ERBB2 amplification. We show that chromosomal copy numbers can only be estimated from SNP array signals or sequencing depths for subclonal tumor samples with simple subclonal architectures under certain assumptions.Electronic supplementary materialThe online version of this article (doi:10.1186/s13059-014-0470-7) contains supplementary material, which is available to authorized users.

show abstract

“…The input data of NSA are the summarized probe signals ( θ A and θ B ) calculated using any summarization method such as dChip [13], RMA [14], CRMA v2 [1], ACNE [15], CalMaTe [16] for Affymetrix arrays or the one developed by [17] for Illumina technology. From these allele specific probe signals the fractions of the B-allele ( β = θ B /( θ A + θ B )) are obtained.…”

Section: Methodsmentioning

confidence: 99%

Getting DNA copy numbers without control samples

Ortiz-Estévez

Aramburu

Rubio

2012

Algorithms Mol Biol

Self Cite

View full text Add to dashboard Cite

BackgroundThe selection of the reference to scale the data in a copy number analysis has paramount importance to achieve accurate estimates. Usually this reference is generated using control samples included in the study. However, these control samples are not always available and in these cases, an artificial reference must be created. A proper generation of this signal is crucial in terms of both noise and bias.We propose NSA (Normality Search Algorithm), a scaling method that works with and without control samples. It is based on the assumption that genomic regions enriched in SNPs with identical copy numbers in both alleles are likely to be normal. These normal regions are predicted for each sample individually and used to calculate the final reference signal. NSA can be applied to any CN data regardless the microarray technology and preprocessing method. It also finds an optimal weighting of the samples minimizing possible batch effects.ResultsFive human datasets (a subset of HapMap samples, Glioblastoma Multiforme (GBM), Ovarian, Prostate and Lung Cancer experiments) have been analyzed. It is shown that using only tumoral samples, NSA is able to remove the bias in the copy number estimation, to reduce the noise and therefore, to increase the ability to detect copy number aberrations (CNAs). These improvements allow NSA to also detect recurrent aberrations more accurately than other state of the art methods.ConclusionsNSA provides a robust and accurate reference for scaling probe signals data to CN values without the need of control samples. It minimizes the problems of bias, noise and batch effects in the estimation of CNs. Therefore, NSA scaling approach helps to better detect recurrent CNAs than current methods. The automatic selection of references makes it useful to perform bulk analysis of many GEO or ArrayExpress experiments without the need of developing a parser to find the normal samples or possible batches within the data. The method is available in the open-source R package NSA, which is an add-on to the aroma.cn framework. http://www.aroma-project.org/addons.

show abstract

CalMaTe: a method and software to improve allele-specific copy number of SNP arrays for downstream segmentation

Abstract: The method is available on CRAN (http://cran.r-project.org/) in the open-source R package calmate, which also includes an add-on to the Aroma Project framework (http://www.aroma-project.org/).

Cited by 19 publications

References 12 publications

Allelic loss of 9p21.3 is a prognostic factor in 1p/19q codeleted anaplastic gliomas

Allelic loss of 9p21.3 is a prognostic factor in 1p/19q codeleted anaplastic gliomas

Deciphering clonality in aneuploid breast tumors using SNP array and sequencing data

Getting DNA copy numbers without control samples

Contact Info

Product

Resources

About