Dataset Information

Framework for quality assessment of whole genome cancer sequences.

ABSTRACT: Bringing together cancer genomes from different projects increases power and allows the investigation of pan-cancer, molecular mechanisms. However, working with whole genomes sequenced over several years in different sequencing centres requires a framework to compare the quality of these sequences. We used the Pan-Cancer Analysis of Whole Genomes cohort as a test case to construct such a framework. This cohort contains whole cancer genomes of 2832 donors from 18 sequencing centres. We developed a non-redundant set of five quality control (QC) measurements to establish a star rating system. These QC measures reflect known differences in sequencing protocol and provide a guide to downstream analyses and allow for exclusion of samples of poor quality. We have found that this is an effective framework of quality measures. The implementation of the framework is available at: https://dockstore.org/containers/quay.io/jwerner_dkfz/pancanqc:1.2.2 .

SUBMITTER: Whalley JP

PROVIDER: S-EPMC7541455 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

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Framework for quality assessment of whole genome cancer sequences.

Whalley Justin P JP Buchhalter Ivo I Rheinbay Esther E Raine Keiran M KM Stobbe Miranda D MD Kleinheinz Kortine K Werner Johannes J Beltran Sergi S Gut Marta M Hübschmann Daniel D Hutter Barbara B Livitz Dimitri D Perry Marc D MD Rosenberg Mara M Saksena Gordon G Trotta Jean-Rémi JR Eils Roland R Gerhard Daniela S DS Campbell Peter J PJ Schlesner Matthias M Gut Ivo G IG

Nature communications 20201007 1

Bringing together cancer genomes from different projects increases power and allows the investigation of pan-cancer, molecular mechanisms. However, working with whole genomes sequenced over several years in different sequencing centres requires a framework to compare the quality of these sequences. We used the Pan-Cancer Analysis of Whole Genomes cohort as a test case to construct such a framework. This cohort contains whole cancer genomes of 2832 donors from 18 sequencing centres. We developed ...[more]

PMID: 33028839

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Project description:BackgroundPhylogenetic methods which do not rely on multiple sequence alignments are important tools in inferring trees directly from completely sequenced genomes. Here, we extend the recently described Genome BLAST Distance Phylogeny (GBDP) strategy to compute phylogenetic trees from all completely sequenced plastid genomes currently available and from a selection of mitochondrial genomes representing the major eukaryotic lineages. BLASTN, TBLASTX, or combinations of both are used to locate high-scoring segment pairs (HSPs) between two sequences from which pairwise similarities and distances are computed in different ways resulting in a total of 96 GBDP variants. The suitability of these distance formulae for phylogeny reconstruction is directly estimated by computing a recently described measure of "treelikeness", the so-called delta value, from the respective distance matrices. Additionally, we compare the trees inferred from these matrices using UPGMA, NJ, BIONJ, FastME, or STC, respectively, with the NCBI taxonomy tree of the taxa under study.ResultsOur results indicate that, at this taxonomic level, plastid genomes are much more valuable for inferring phylogenies than are mitochondrial genomes, and that distances based on breakpoints are of little use. Distances based on the proportion of "matched" HSP length to average genome length were best for tree estimation. Additionally we found that using TBLASTX instead of BLASTN and, particularly, combining TBLASTX and BLASTN leads to a small but significant increase in accuracy. Other factors do not significantly affect the phylogenetic outcome. The BIONJ algorithm results in phylogenies most in accordance with the current NCBI taxonomy, with NJ and FastME performing insignificantly worse, and STC performing as well if applied to high quality distance matrices. delta values are found to be a reliable predictor of phylogenetic accuracy.ConclusionUsing the most treelike distance matrices, as judged by their delta values, distance methods are able to recover all major plant lineages, and are more in accordance with Apicomplexa organelles being derived from "green" plastids than from plastids of the "red" type. GBDP-like methods can be used to reliably infer phylogenies from different kinds of genomic data. A framework is established to further develop and improve such methods. delta values are a topology-independent tool of general use for the development and assessment of distance methods for phylogenetic inference.

Dataset Information

Framework for quality assessment of whole genome cancer sequences.

Publications

Framework for quality assessment of whole genome cancer sequences.

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