Computational protocol: Nonlinear tumor evolution from dysplastic nodules to hepatocellular carcinoma

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Protocol publication

[…] Sequencing reads were aligned to the UCSC hg19 reference genome using Burrows-Wheeler Aligner [], version 0.6.2 with default settings. PCR duplications are marked by Picard-tools-1.8 (http://picard.sourceforge.net/), followed by data cleanup with GATK-2.2.9 []. Point mutations were then identified by the MuTect tool (https://github.com/broadinstitute/mutect) using all the 12 nodules and their corresponding cirrhotic tissues (). Perl script and Annovar were used to annotate the variants and search the known somatic mutations (around 1.3 million) using COSMIC v.64 (http://cancer.sanger.ac.uk/) and TCGA. High confidence mutations were selected with a threshold read depth of ≥ 20, a variant allele frequency of ≥ 20%, and sequencing quality check. We checked the sequencing quality by visualizing mutations in genome regions using the Integrative Genome Viewer tool (http://www.broadinstitute.org/igv/). Among numerous CNV callers, EXCAVATOR showed the best performance in detect CNVs [] []. In order to assess a stepwise increasing pattern of mutations and CNV, we obtained P values from 10,000 permutations under increasing alternatives []. Their significance was then tested with rates of high confidence mutations and the number of CNVs per chromosome, respectively. Phylogenetic analysis was performed based on copy number profiles. We generated the binary sequence by binning copy number regions at a bin size of 100,000 bp. The phylogenetic tree was then analyzed by Wagner parsimony method []. […]

Pipeline specifications

Software tools BWA, Picard, GATK, MuTect, ANNOVAR, IGV, EXCAVATOR
Databases TCGA Data Portal
Applications Phylogenetics, WES analysis, Genome data visualization
Organisms Homo sapiens, Cucumber necrosis virus
Diseases Carcinoma, Hepatocellular, Neoplasms, Thyroid Nodule
Chemicals Nucleotides