Ploidy- and Purity-Adjusted Allele-Specific DNA Analysis Using CLONETv2.

Davide Prandi,Francesca Demichelis

doi:10.1002/cpbi.81

Davide Prandi, Francesca Demichelis

Open Access

https://doi.org/10.1002/cpbi.81

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Abstract

High‐throughput DNA sequencing technology provides base‐level and statistically rich information about the genomic content of a sample. In the contexts of cancer research and precision oncology, thousands of genomes from paired tumor and matched normal samples are profiled and processed to determine somatic copy‐number changes and single‐nucleotide variations. Higher‐order informative analyses, in the form of allele‐specific copy‐number assessments or subclonality quantification, require reliable estimates of tumor DNA ploidy and tumor cellularity. CLONETv2 provides a complete set of functions to process matched normal and tumor pairs using patient‐specific genotype data, is independent of low‐level tools (e.g., aligner, segmentation algorithm, mutation caller) and offers high‐level functions to compute allele‐specific copy number from segmented data and to identify subclonal population in the input sample. CLONETv2 is applicable to whole‐genome, whole‐exome and targeted sequencing data generated either from tissue or from liquid biopsy samples. © 2019 The Authors.

Highlights

Massive sequencing efforts, as by The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC), have generated a comprehensive collection of sequenced genomes of cancer patients, opening a new era for genomics
DNA admixture refers to the amount of non-cancer cells in a tumor sample, while ploidy represents the average number of chromosomes set in a cell
In Beltran et al (Beltran et al, 2016), CLONET was extended to provide allele specific copy number data from whole exome sequencing experiments; for each genomic segment in each study cohort tumor, the study reports the number of copies of each allele using ploidy, DNA admixture, LogR and the allelic fraction (AF) of informative single-nucleotide polymorphisms (SNP)

Summary

INTRODUCTION

As by The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC), have generated a comprehensive collection of sequenced genomes of cancer patients, opening a new era for genomics. In Beltran et al (Beltran et al, 2016), CLONET was extended to provide allele specific copy number data from whole exome sequencing experiments; for each genomic segment in each study cohort tumor, the study reports the number of copies of each allele using ploidy, DNA admixture, LogR and the AF of informative SNPs. In Faltas et al (Faltas et al, 2016), clonality analysis capability of CLONET was improved to account for complex allele specific combinations and single nucleotide variants (SNVs). Upon definition of ploidy and DNA admixture, Equation 1 completely defines the absolute copy number of both alleles We will exploit this capability in Support Protocol 2, where Equation 1 is used to plot expected beta and log ratio against estimated values. Prepare tumor segmented data in file tumor_segments.txt and with columns compatible with parameter seg_tb described above

Load input files

Compute beta for each input segment with default parameters

Compute basic beta vs LogR plot

Background

Findings

Significance Statement