Deconvolving tumor purity and ploidy by integrating copy number alterations and loss of heterozygosity
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PROVIDER: S-EPMC4402367 | biostudies-literature | 2014 Oct
REPOSITORIES: biostudies-literature
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Project description:MotivationNext-generation sequencing (NGS) has revolutionized the study of cancer genomes. However, the reads obtained from NGS of tumor samples often consist of a mixture of normal and tumor cells, which themselves can be of multiple clonal types. A prominent problem in the analysis of cancer genome sequencing data is deconvolving the mixture to identify the reads associated with tumor cells or a particular subclone of tumor cells. Solving the problem is, however, challenging because of the so-called 'identifiability problem', where different combinations of tumor purity and ploidy often explain the sequencing data equally well.ResultsWe propose a new model to resolve the identifiability problem by integrating two types of sequencing information-somatic copy number alterations and loss of heterozygosity-within a unified probabilistic framework. We derive algorithms to solve our model, and implement them in a software package called PyLOH. We benchmark the performance of PyLOH using both simulated data and 12 breast cancer sequencing datasets and show that PyLOH outperforms existing methods in disambiguating the identifiability problem and estimating tumor purity.Availability and implementationThe PyLOH package is written in Python and is publicly available at https://github.com/uci-cbcl/PyLOH.Contactxhx@ics.uci.eduSupplementary informationSupplementary data are available at Bioinformatics online.
| S-EPMC4103592 | biostudies-literature
Project description:Treatment choices for cervical cancer are primarily based on clinical FIGO stage and the post-operative evaluation of prognostic parameters including tumor diameter, parametrial and lymph node involvement, vaso-invasion, infiltration depth, and histological type. The aim of this study was to evaluate genomic changes in bulky cervical tumors and their relation to clinical parameters, using single nucleotide polymorphism (SNP)-analysis. Flow-sorted tumor cells and patient-matched normal cells were extracted from 81 bulky cervical tumors. DNA-index (DI) measurement and whole genome SNP-analysis were performed. Data were analyzed to detect copy number alterations (CNA) and allelic balance state: balanced, imbalanced or pure LOH, and their relation to clinical parameters. The DI varied from 0.92-2.56. Pure LOH was found in ≥40% of samples on chromosome-arms 3p, 4p, 6p, 6q, and 11q, CN gains in >20% on 1q, 3q, 5p, 8q, and 20q, and losses on 2q, 3p, 4p, 11q, and 13q. Over 40% showed gain on 3q. The only significant differences were found between histological types (squamous, adeno and adenosquamous) in the lesser allele intensity ratio (LAIR) (p = 0.035) and in the CNA analysis (p = 0.011). More losses were found on chromosome-arm 2q (FDR = 0.004) in squamous tumors and more gains on 7p, 7q, and 9p in adenosquamous tumors (FDR = 0.006, FDR = 0.004, and FDR = 0.029). Whole genome analysis of bulky cervical cancer shows widespread changes in allelic balance and CN. The overall genetic changes and CNA on specific chromosome-arms differed between histological types. No relation was found with the clinical parameters that currently dictate treatment choice.
| S-EPMC3706587 | biostudies-literature
Project description:MotivationTumor purity and ploidy have a substantial impact on next-gen sequence analyses of tumor samples and may alter the biological and clinical interpretation of results. Despite the existence of several computational methods that are dedicated to estimate tumor purity and/or ploidy from The Cancer Genome Atlas (TCGA) tumor-normal whole-genome-sequencing (WGS) data, an accurate, fast and fully-automated method that works in a wide range of sequencing coverage, level of tumor purity and level of intra-tumor heterogeneity, is still missing.ResultsWe describe a computational method called Accurity that infers tumor purity, tumor cell ploidy and absolute allelic copy numbers for somatic copy number alterations (SCNAs) from tumor-normal WGS data by jointly modelling SCNAs and heterozygous germline single-nucleotide-variants (HGSNVs). Results from both in silico and real sequencing data demonstrated that Accurity is highly accurate and robust, even in low-purity, high-ploidy and low-coverage settings in which several existing methods perform poorly. Accounting for tumor purity and ploidy, Accurity significantly increased signal/noise gaps between different copy numbers. We are hopeful that Accurity is of clinical use for identifying cancer diagnostic biomarkers.Availability and implementationAccurity is implemented in C++/Rust, available at http://www.yfish.org/software/.Supplementary informationSupplementary data are available at Bioinformatics online.
| S-EPMC9881684 | biostudies-literature
Project description:VCF2CNA is a tool (Linux commandline or web-interface) for copy-number alteration (CNA) analysis and tumor purity estimation of paired tumor-normal VCF variant file formats. It operates on whole genome and whole exome datasets. To benchmark its performance, we applied it to 46 adult glioblastoma and 146 pediatric neuroblastoma samples sequenced by Illumina and Complete Genomics (CGI) platforms respectively. VCF2CNA was highly consistent with a state-of-the-art algorithm using raw sequencing data (mean F1-score = 0.994) in high-quality whole genome glioblastoma samples and was robust to uneven coverage introduced by library artifacts. In the whole genome neuroblastoma set, VCF2CNA identified MYCN high-level amplifications in 31 of 32 clinically validated samples compared to 15 found by CGI's HMM-based CNA model. Moreover, VCF2CNA achieved highly consistent CNA profiles between WGS and WXS platforms (mean F1 score 0.97 on a set of 15 rhabdomyosarcoma samples). In addition, VCF2CNA provides accurate tumor purity estimates for samples with sufficient CNAs. These results suggest that VCF2CNA is an accurate, efficient and platform-independent tool for CNA and tumor purity analyses without accessing raw sequence data.
| S-EPMC6637131 | biostudies-literature
Project description:The landscape of chromosomal aberrations in the tumor cells of the patients with B-ALL is diverse and can influence the outcome of the disease. Molecular karyotyping at the onset of the disease using chromosomal microarray (CMA) is advisable to identify additional molecular factors associated with the prognosis of the disease. Molecular karyotyping data for 36 patients with Ph-negative B-ALL who received therapy according to the ALL-2016 protocol are presented. We analyzed copy number alterations and their prognostic significance for CDKN2A/B, DMRTA, DOCK8, TP53, SMARCA2, PAX5, XPA, FOXE1, HEMGN, USP45, RUNX1, NF1, IGF2BP1, ERG, TMPRSS2, CRLF2, FGFR3, FLNB, IKZF1, RUNX2, ARID1B, CIP2A, PIK3CA, ATM, RB1, BIRC3, MYC, IKZF3, ETV6, ZNF384, PTPRJ, CCL20, PAX3, MTCH2, TCF3, IKZF2, BTG1, BTG2, RAG1, RAG2, ELK3, SH2B3, EP300, MAP2K2, EBI3, MEF2D, MEF2C, CEBPA, and TBLXR1 genes, choosing t(4;11) and t(7;14) as reference events. Of the 36 patients, only 5 (13.8%) had a normal molecular karyotype, and 31 (86.2%) were found to have various molecular karyotype abnormalities-104 deletions, 90 duplications or amplifications, 29 cases of cnLOH and 7 biallelic/homozygous deletions. We found that 11q22-23 duplication involving the BIRC3, ATM and MLL genes was the most adverse prognostic event in the study cohort.
| S-EPMC10744257 | biostudies-literature
Project description:MotivationThe ability to detect copy-number variation (CNV) and loss of heterozygosity (LOH) from exome sequencing data extends the utility of this powerful approach that has mainly been used for point or small insertion/deletion detection.ResultsWe present ExomeCNV, a statistical method to detect CNV and LOH using depth-of-coverage and B-allele frequencies, from mapped short sequence reads, and we assess both the method's power and the effects of confounding variables. We apply our method to a cancer exome resequencing dataset. As expected, accuracy and resolution are dependent on depth-of-coverage and capture probe design.AvailabilityCRAN package 'ExomeCNV'.Contactfsathira@fas.harvard.edu; snelson@ucla.eduSupplementary informationSupplementary data are available at Bioinformatics online.
| S-EPMC3179661 | biostudies-literature
Project description:BackgroundCopy number alterations (CNAs), due to their large impact on the genome, have been an important contributing factor to oncogenesis and metastasis. Detecting genomic alterations from the shallow-sequencing data of a low-purity tumor sample remains a challenging task.ResultsWe introduce Accucopy, a method to infer total copy numbers (TCNs) and allele-specific copy numbers (ASCNs) from challenging low-purity and low-coverage tumor samples. Accucopy adopts many robust statistical techniques such as kernel smoothing of coverage differentiation information to discern signals from noise and combines ideas from time-series analysis and the signal-processing field to derive a range of estimates for the period in a histogram of coverage differentiation information. Statistical learning models such as the tiered Gaussian mixture model, the expectation-maximization algorithm, and sparse Bayesian learning were customized and built into the model. Accucopy is implemented in C++ /Rust, packaged in a docker image, and supports non-human samples, more at http://www.yfish.org/software/ .ConclusionsWe describe Accucopy, a method that can predict both TCNs and ASCNs from low-coverage low-purity tumor sequencing data. Through comparative analyses in both simulated and real-sequencing samples, we demonstrate that Accucopy is more accurate than Sclust, ABSOLUTE, and Sequenza.
| S-EPMC7811225 | biostudies-literature
Project description:Using whole-exome sequencing (WES) for the detection of chromosomal aberrations from tumor samples has become increasingly popular, as it is cost-effective and time efficient. However, factors which present in WES tumor samples, including diversity in exon size, batch effect and tumor impurity, can complicate the identification of somatic mutation in each region of the exon. To address these issues, the authors of the present study have developed a novel method, PECNV, for the detection of genomic copy number variants and loss of heterozygosity in WES datasets. PECNV combines normalized logarithm ratio of read counts (Log Ratio) and B allele frequency (BAF), and then employs expectation maximization (EM) algorithm to estimate parameters involved in the models. A comprehensive assessment of PECNV of PECNV was performed by analyzing simulated datasets contaminated with different normal cell proportion and eight real primary triple-negative breast cancer samples. PECNV demonstrated superior results compared with ExomeCNV and EXCAVATOR for the detection of genomic aberrations in WES data.
| S-EPMC6126229 | biostudies-literature
Project description:BackgroundSomatic mosaicism denotes the presence of genetically distinct populations of somatic cells in one individual who has developed from a single fertilised oocyte. Mosaicism may result from a mutation that occurs during postzygotic development and is propagated to only a subset of the adult cells. Our aim was to investigate both somatic mosaicism for copy-neutral loss of heterozygosity (cn-LOH) events and DNA copy number variations (CNVs) in fully differentiated tissues.ResultsWe studied panels of tissue samples (11-12 tissues per individual) from four autopsy subjects using high-resolution Illumina HumanOmniExpress-12 BeadChips to reveal the presence of possible intra-individual tissue-specific cn-LOH and CNV patterns. We detected five mosaic cn-LOH regions >5 Mb in some tissue samples in three out of four individuals. We also detected three CNVs that affected only a portion of the tissues studied in one out of four individuals. These three somatic CNVs range from 123 to 796 kb and are also found in the general population. An attempt was made to explain the succession of genomic events that led to the observed somatic genetic mosaicism under the assumption that the specific mosaic patterns of CNV and cn-LOH changes reflect their formation during the postzygotic embryonic development of germinal layers and organ systems.ConclusionsOur results give further support to the idea that somatic mosaicism for CNVs, and also cn-LOHs, is a common phenomenon in phenotypically normal humans. Thus, the examination of only a single tissue might not provide enough information to diagnose potentially deleterious CNVs within an individual. During routine CNV and cn-LOH analysis, DNA derived from a buccal swab can be used in addition to blood DNA to get information about the CNV/cn-LOH content in tissues of both mesodermal and ectodermal origin. Currently, the real frequency and possible phenotypic consequences of both CNVs and cn-LOHs that display somatic mosaicism remain largely unknown. To answer these questions, future studies should involve larger cohorts of individuals and a range of tissues.
| S-EPMC4573927 | biostudies-literature
Project description:MotivationDetection and quantification of the absolute DNA copy number alterations in tumor cells is challenging because the DNA specimen is extracted from a mixture of tumor and normal stromal cells. Estimates of tumor purity and ploidy are necessary to correctly infer copy number, and ploidy may itself be a prognostic factor in cancer progression. As deep sequencing of the exome or genome has become routine for characterization of tumor samples, in this work, we aim to develop a simple and robust algorithm to infer purity, ploidy and absolute copy numbers in whole numbers for tumor cells from sequencing data.ResultsA simulation study shows that estimates have reasonable accuracy, and that the algorithm is robust against the presence of segmentation errors and subclonal populations. We validated our algorithm against a panel of cell lines with experimentally determined ploidy. We also compared our algorithm with the well-established single-nucleotide polymorphism array-based method called ABSOLUTE on three sets of tumors of different types. Our method had good performance on these four benchmark datasets for both purity and ploidy estimates, and may offer a simple solution to copy number alteration quantification for cancer sequencing projects.Availability and implementationThe R package absCNseq is available from http://biostats.mcc.ucsd.edu/files/absCNseq_1.0.tar.gz CONTACT: kmesser@ucsd.edu Supplementary information: Supplementary data are available at Bioinformatics online.
| S-EPMC6280749 | biostudies-literature