AbstractSelecting proper genome assembly is key for downstream analysis in genomics studies. However, the availability of many genome assembly tools and the huge variety of their running parameters challenge this task. The existing online evaluation tools are limited to specific taxa or provide just a one-sided view on the assembly quality. We present WebQUAST, a web server for multifaceted quality assessment and comparison of genome assemblies based on the state-of-the-art QUAST tool. The server is freely available at https://www.ccb.uni-saarland.de/quast/. WebQUAST can handle an unlimited number of genome assemblies and evaluate them against a user-provided or pre-loaded reference genome or in a completely reference-free fashion. We demonstrate key WebQUAST features in three common evaluation scenarios: assembly of an unknown species, a model organism, and a close variant of it.

The value of high-throughput germline genetic testing is increasingly recognized in clinical cancer care. Disease-associated germline variants in cancer patients are important for risk management and surveillance, surgical decisions, and can also have major implications for treatment strategies since many are in DNA repair genes. With the increasing availability of high-throughput DNA sequencing in cancer clinics and research, there is thus a need to provide clinically oriented sequencing reports for germline variants and their potential therapeutic relevance on a per-patient basis. To meet this need we have developed the Cancer Predisposition Sequencing Reporter (CPSR), an open-source computational workflow that generates a structured report of germline variants identified in known cancer predisposition genes, highlighting markers of therapeutic, prognostic, and diagnostic relevance. A fully automated variant classification procedure based on more than 30 refined ACMG criteria represents an integral part of the workflow. Importantly, the set of cancer predisposition genes profiled in the report can be flexibly chosen from more than 40 virtual gene panels established by scientific experts, enabling customization of the report for different screening purposes and clinical contexts. The report can be configured to also list actionable secondary variant findings as recommended by ACMG, as well as the status of low-risk variants from genome-wide association studies in cancer. CPSR demonstrates superior sensitivity and comparable specificity for the detection of pathogenic variants when compared to existing algorithms. Technically, the tool is implemented in Python/R, and is freely available through Docker technology. Source code, documentation, example reports, and installation instructions are accessible via the project GitHub page: https://github.com/sigven/cpsr.

Motivation: ​ While ​ somatic mutagenesis is the driving force of most human cancers, the germline genome is of significant clinical value in several tumor types. Cancer predisposition variants are important for risk management and surveillance, and can also have major implications for treatment strategies since many are in DNA repair genes. Following the incorporation of high-throughput DNA sequencing in cancer clinics and research, there is thus a need to provide clinically oriented sequencing reports for risk-associated germline variants and their potential therapeutic relevance on a per patient basis. Results: We have developed the Cancer Predisposition Sequencing Reporter (CPSR), an open-source computational workflow that provides a structured report of germline variants identified in known cancer predisposition genes. Building upon existing knowledge sources and variant databases relevant for cancer susceptibility, CPSR combines a transparent and cancer-dedicated scoring scheme for variant pathogenicity ( ​ American College of Medical Genetics and Genomics, ​ ACMG) with existing variant classifications from ClinVar in order to derive a structured and prioritised list of variant findings. The workflow outputs a comprehensive and interactive HTML report that highlights putative markers of therapeutic, prognostic and diagnostic relevance. Importantly, the set of cancer predisposition genes profiled in the report can be flexibly chosen from nearly 40 virtual gene panels established by scientific experts, enabling a customization of the report for different screening purposes. The report can be configured to also list potential incidental variant findings as recommended by ACMG, as well as the status of low-risk variants from genome-wide association studies in cancer.

Genome assemblies of Yeast (S. cerevisiae, genome size: 12.1 Mb): ABruijn, Canu, FALCON, MaSuRCA (from Illumina pair-ends and PacBio) Worm (C. elegans,genome size: 100.3 Mb): ABruijn, Canu, FALCON, MaSuRCA (from Illumina pair-ends and PacBio) Fruit fly (D. melanogaster, genome size: 137.6 Mb): ABySS2, MaSuRCA, MEGAHIT, Meraculous, Platanus, SOAPdenovo2, SPAdes (from Illumina pair-ends and mate-pairs) Each pack is accompanied with the theoretically optimal assembly created with QUAST-LG. For more information please visit http://cab.spbu.ru/software/quast-lg/ or write to quast.support@cab.spbu.ru.

Current understanding of the mutation spectrum of relapsed/refractory (RR) tumors is limited. We performed whole exome sequencing (WES) on 47 diffuse large B cell lymphoma (DLBCL) tumors that persisted after R-CHOP treatment, 8 matched to primary biopsies. We compared genomic alterations from the RR cohort against two treatment-naïve DLBCL cohorts (n=112). While the overall number and types of mutations did not differ significantly, we identified frequency changes in DLBCL driver genes. The overall frequency of MYD88 mutant samples increased (12% to 19%), but we noted a decrease in p.L265P (8% to 4%) and increase in p.S219C mutations (2% to 6%). CARD11 p.D230N, PIM1 p.K115N and CD79B p.Y196C mutations were not observed in the RR cohort, although these mutations were prominent in the primary DLBCL samples. We observed an increase in BCL2 mutations (21% to 38% of samples), BCL2 amplifications (3% to 6% of samples) and CREBBP mutations (31% to 42% of samples) in the RR cohort, supported by acquisition of mutations in these genes in relapsed compared to diagnostic biopsies from the same patient. These increases may reflect the genetic characteristics of R-CHOP RR tumors expected to be enriched for during clinical trial enrollment. These findings hold significance for a number of emerging targeted therapies aligned to genetic targets and biomarkers in DLBCL, reinforcing the importance of time-of-treatment biomarker screening during DLBCL therapy selection.

: Data visualization plays an increasingly important role in NGS data analysis. With advances in both sequencing and computational technologies, it has become a new bottleneck in genomics studies. Indeed, evaluation of de novo genome assemblies is one of the areas that can benefit from the visualization. However, even though multiple quality assessment methods are now available, existing visualization tools are hardly suitable for this purpose. Here, we present Icarus-a novel genome visualizer for accurate assessment and analysis of genomic draft assemblies, which is based on the tool QUAST. Icarus can be used in studies where a related reference genome is available, as well as for non-model organisms. The tool is available online and as a standalone application. AVAILABILITY AND IMPLEMENTATION http://cab.spbu.ru/software/icarus CONTACT: aleksey.gurevich@spbu.ruSupplementary information: Supplementary data are available at Bioinformatics online.

UNLABELLED:During the past years we have witnessed the rapid development of new metagenome assembly methods. Although there are many benchmark utilities designed for single-genome assemblies, there is no well-recognized evaluation and comparison tool for metagenomic-specific analogues. In this article, we present MetaQUAST, a modification of QUAST, the state-of-the-art tool for genome assembly evaluation based on alignment of contigs to a reference. MetaQUAST addresses such metagenome datasets features as (i) unknown species content by detecting and downloading reference sequences, (ii) huge diversity by giving comprehensive reports for multiple genomes and (iii) presence of highly relative species by detecting chimeric contigs. We demonstrate MetaQUAST performance by comparing several leading assemblers on one simulated and two real datasets.AVAILABILITY AND IMPLEMENTATION:http://bioinf.spbau.ru/metaquastCONTACT:aleksey.gurevich@spbu.ruSUPPLEMENTARY INFORMATION:Supplementary data are available at Bioinformatics online.

SUMMARY:Limitations of genome sequencing techniques have led to dozens of assembly algorithms, none of which is perfect. A number of methods for comparing assemblers have been developed, but none is yet a recognized benchmark. Further, most existing methods for comparing assemblies are only applicable to new assemblies of finished genomes; the problem of evaluating assemblies of previously unsequenced species has not been adequately considered. Here, we present QUAST-a quality assessment tool for evaluating and comparing genome assemblies. This tool improves on leading assembly comparison software with new ideas and quality metrics. QUAST can evaluate assemblies both with a reference genome, as well as without a reference. QUAST produces many reports, summary tables and plots to help scientists in their research and in their publications. In this study, we used QUAST to compare several genome assemblers on three datasets. QUAST tables and plots for all of them are available in the Supplementary Material, and interactive versions of these reports are on the QUAST website. AVAILABILITY:http://bioinf.spbau.ru/quast . SUPPLEMENTARY INFORMATION:Supplementary data are available at Bioinformatics online.