Computational protocol: Single nucleotide variant profiles of viable single circulating tumour cells reveal CTC behaviours in breast cancer

Similar protocols

Protocol publication

[…] Adapter sequences and low-quality reads were removed from the raw sequence data using Cutadapt () and sickle (http://github.com/najoshi/sickle/) software. After the clean data were aligned to hg19 using the Burrows-Wheeler Aligner (BWA) (), SAM files were produced. Picard tools (http://broadinstitute.github.io/picard/) were used to transform the SAM files to a bam format and to sort and remove PCR duplications. In addition with the help of the Genome Analysis Toolkit (GATK) pipeline (), the original bam files were processed for local Indel realignment, base quality estimation and recalibration for further analysis.Somatic mutation calling was performed. For whole exome data, VarScan2 () combined with the JointSNVMix2 () algorithm were used to identify somatic mutations and the candidates were merged, while whole genomic data somatic mutation calling used only the VarScan2 algorithm. To reduce false-positive calls, the candidate calls were filtered using the following criteria: i) zero mutant reads detected in the germline sample; ii) at least 10X accumulated coverage for both the forward and reverse reads of the tumour sample in the mutant alleles; and iii) the nearest adjacent mutant base was at least 100 bp away in the same sample. The filtered SNVs were annotated using Oncotator (), and the variant allele fraction (VAF) was calculated as follows: VAF = read counts that covered the mutant position/all read counts that covered the position for data from a single cell.To determine the copy number, we used Ginkgo (http://qb.cshl.edu/ginkgo), an open-source web platform that specifically analyses single-cell copy number variants (CNVs), and two R packages (HMMcopy and DNAcopy), with hg19 as the reference genome. […]

Pipeline specifications

Software tools cutadapt, BWA, Picard, GATK, VarScan, JointSNVMix, Oncotator, HMMcopy
Applications WGS analysis, WES analysis
Organisms Human poliovirus 1 Mahoney, Homo sapiens
Diseases Breast Neoplasms, Neoplasms, Ocular Motility Disorders
Chemicals Nucleotides