scholarly journals PyClone-VI: scalable inference of clonal population structures using whole genome data

2020 ◽  
Vol 21 (1) ◽  
Author(s):  
Sierra Gillis ◽  
Andrew Roth
Keyword(s):  
Malignant Cell ◽  
Whole Genome Sequencing Data ◽  
Whole Genome ◽  
Cancer Evolution ◽  
Sequencing Data ◽  
Computationally Efficient ◽  
Clonal Population ◽  
Genome Data ◽  
Population Structures ◽  
Clonal Population Structure

Abstract Background At diagnosis tumours are typically composed of a mixture of genomically distinct malignant cell populations. Bulk sequencing of tumour samples coupled with computational deconvolution can be used to identify these populations and study cancer evolution. Existing computational methods for populations deconvolution are slow and/or potentially inaccurate when applied to large datasets generated by whole genome sequencing data. Results We describe PyClone-VI, a computationally efficient Bayesian statistical method for inferring the clonal population structure of cancers. We demonstrate the utility of the method by analyzing data from 1717 patients from PCAWG study and 100 patients from the TRACERx study. Conclusions Our proposed method is 10–100× times faster than existing methods, while providing results which are as accurate. Software implementing our method is freely available https://github.com/Roth-Lab/pyclone-vi.

scholarly journals PyClone-VI: Scalable inference of clonal population structures using whole genome data

2020 ◽  
Author(s):  
Sierra Gillis ◽  
Andrew Roth
Keyword(s):  
Population Structure ◽  
Statistical Method ◽  
Whole Genome ◽  
Computationally Efficient ◽  
Clonal Population ◽  
Link Type ◽  
Genome Data ◽  
Population Structures ◽  
Scalable Inference ◽  
Clonal Population Structure

AbstractWe describe PyClone-VI, a computationally efficient Bayesian statistical method for inferring the clonal population structure of cancers. Our proposed method is 10-100x times faster than existing methods, while providing results which are as accurate. We demonstrate the utility of the method by analyzing data from 1717 patients from PCAWG study and 100 patients from the TRACERx study. Software implementing our method is freely available https://github.com/Roth-Lab/pyclone-vi.

scholarly journals Use of Whole Genome Sequencing Data for a First in Silico Specificity Evaluation of the RT-qPCR Assays Used for SARS-CoV-2 Detection

2020 ◽  
Vol 21 (15) ◽  
pp. 5585
Author(s):  
Mathieu Gand ◽  
Kevin Vanneste ◽  
Isabelle Thomas ◽  
Steven Van Gucht ◽  
Arnaud Capron ◽  
...  
Keyword(s):  
In Silico ◽  
Protein S ◽  
Whole Genome Sequencing Data ◽  
Whole Genome ◽  
Sequencing Data ◽  
Viral Genomes ◽  
Genome Data ◽  
Gene Coding ◽  
Control And Prevention ◽  
The Impact

The current COronaVIrus Disease 2019 (COVID-19) pandemic started in December 2019. COVID-19 cases are confirmed by the detection of SARS-CoV-2 RNA in biological samples by RT-qPCR. However, limited numbers of SARS-CoV-2 genomes were available when the first RT-qPCR methods were developed in January 2020 for initial in silico specificity evaluation and to verify whether the targeted loci are highly conserved. Now that more whole genome data have become available, we used the bioinformatics tool SCREENED and a total of 4755 publicly available SARS-CoV-2 genomes, downloaded at two different time points, to evaluate the specificity of 12 RT-qPCR tests (consisting of a total of 30 primers and probe sets) used for SARS-CoV-2 detection and the impact of the virus’ genetic evolution on four of them. The exclusivity of these methods was also assessed using the human reference genome and 2624 closely related other respiratory viral genomes. The specificity of the assays was generally good and stable over time. An exception is the first method developed by the China Center for Disease Control and prevention (CDC), which exhibits three primer mismatches present in 358 SARS-CoV-2 genomes sequenced mainly in Europe from February 2020 onwards. The best results were obtained for the assay of Chan et al. (2020) targeting the gene coding for the spiking protein (S). This demonstrates that our user-friendly strategy can be used for a first in silico specificity evaluation of future RT-qPCR tests, as well as verifying that the former methods are still capable of detecting circulating SARS-CoV-2 variants.

scholarly journals Blood group typing from whole-genome sequencing data

PLoS ONE ◽  
2020 ◽  
Vol 15 (11) ◽  
pp. e0242168
Author(s):  
Julien Paganini ◽  
Peter L. Nagy ◽  
Nicholas Rouse ◽  
Philippe Gouret ◽  
Jacques Chiaroni ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Blood Group ◽  
Genome Sequencing ◽  
Hla Typing ◽  
Next Generation Sequencing Data ◽  
Whole Genome Sequencing Data ◽  
Whole Genome ◽  
Sequencing Data ◽  
Personalized Care ◽  
Genome Data

Many questions can be explored thanks to whole-genome data. The aim of this study was to overcome their main limits, software availability and database accuracy, and estimate the feasibility of red blood cell (RBC) antigen typing from whole-genome sequencing (WGS) data. We analyzed whole-genome data from 79 individuals for HLA-DRB1 and 9 RBC antigens. Whole-genome sequencing data was analyzed with software allowing phasing of variable positions to define alleles or haplotypes and validated for HLA typing from next-generation sequencing data. A dedicated database was set up with 1648 variable positions analyzed in KEL (KEL), ACKR1 (FY), SLC14A1 (JK), ACHE (YT), ART4 (DO), AQP1 (CO), CD44 (IN), SLC4A1 (DI) and ICAM4 (LW). Whole-genome sequencing typing was compared to that previously obtained by amplicon-based monoallelic sequencing and by SNaPshot analysis. Whole-genome sequencing data were also explored for other alleles. Our results showed 93% of concordance for blood group polymorphisms and 91% for HLA-DRB1. Incorrect typing and unresolved results confirm that WGS should be considered reliable with read depths strictly above 15x. Our results supported that RBC antigen typing from WGS is feasible but requires improvements in read depth for SNV polymorphisms typing accuracy. We also showed the potential for WGS in screening donors with rare blood antigens, such as weak JK alleles. The development of WGS analysis in immunogenetics laboratories would offer personalized care in the management of RBC disorders.

scholarly journals PEMapper and PECaller provide a simplified approach to whole-genome sequencing

2017 ◽  
Vol 114 (10) ◽  
pp. E1923-E1932 ◽  
Author(s):  
H. Richard Johnston ◽  
Pankaj Chopra ◽  
Thomas S. Wingo ◽  
Viren Patel ◽  
Michael P. Epstein ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Whole Genome Sequencing Data ◽  
Whole Genome ◽  
Sequencing Data ◽  
Computationally Efficient ◽  
Network Resources ◽  
Simplified Approach ◽  
Statistical Framework ◽  
Genome Analysis Toolkit

The analysis of human whole-genome sequencing data presents significant computational challenges. The sheer size of datasets places an enormous burden on computational, disk array, and network resources. Here, we present an integrated computational package, PEMapper/PECaller, that was designed specifically to minimize the burden on networks and disk arrays, create output files that are minimal in size, and run in a highly computationally efficient way, with the single goal of enabling whole-genome sequencing at scale. In addition to improved computational efficiency, we implement a statistical framework that allows for a base by base error model, allowing this package to perform as well or better than the widely used Genome Analysis Toolkit (GATK) in all key measures of performance on human whole-genome sequences.

scholarly journals PEMapper / PECaller: A simplified approach to whole-genome sequencing

2016 ◽  
Author(s):  
H Richard Johnston ◽  
Pankaj Chopra ◽  
Thomas S Wingo ◽  
Viren Patel ◽  
Michael P Epstein ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Whole Genome Sequencing Data ◽  
Whole Genome ◽  
Sequencing Data ◽  
Computationally Efficient ◽  
Network Resources ◽  
Simplified Approach ◽  
Statistical Framework ◽  
Genome Analysis Toolkit

ABSTRACTThe analysis of human whole-genome sequencing data presents significant computational challenges. The sheer size of datasets places an enormous burden on computational, disk array, and network resources. Here we present an integrated computational package, PEMapper/PECaller, that was designed specifically to minimize the burden on networks and disk arrays, create output files that are minimal in size, and run in a highly computationally efficient way, with the single goal of enabling whole-genome sequencing at scale. In addition to improved computational efficiency, we implement a novel statistical framework that allows for a base-by-base error model, allowing this package to perform as well or better than the widely used Genome Analysis Toolkit (GATK) in all key measures of performance on human whole-genome sequences.

scholarly journals Whole genome sequencing reveals high differentiation, low levels of genetic diversity and short runs of homozygosity among Swedish wels catfish

Heredity ◽  
2021 ◽  
Author(s):  
Axel Jensen ◽  
Mette Lillie ◽  
Kristofer Bergström ◽  
Per Larsson ◽  
Jacob Höglund
Keyword(s):  
Genetic Diversity ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Whole Genome Sequencing Data ◽  
Peripheral Populations ◽  
Whole Genome ◽  
Runs Of Homozygosity ◽  
Sequencing Data ◽  
Isolated Populations ◽  
Native Populations

AbstractThe use of genetic markers in the context of conservation is largely being outcompeted by whole-genome data. Comparative studies between the two are sparse, and the knowledge about potential effects of this methodology shift is limited. Here, we used whole-genome sequencing data to assess the genetic status of peripheral populations of the wels catfish (Silurus glanis), and discuss the results in light of a recent microsatellite study of the same populations. The Swedish populations of the wels catfish have suffered from severe declines during the last centuries and persists in only a few isolated water systems. Fragmented populations generally are at greater risk of extinction, for example due to loss of genetic diversity, and may thus require conservation actions. We sequenced individuals from the three remaining native populations (Båven, Emån, and Möckeln) and one reintroduced population of admixed origin (Helge å), and found that genetic diversity was highest in Emån but low overall, with strong differentiation among the populations. No signature of recent inbreeding was found, but a considerable number of short runs of homozygosity were present in all populations, likely linked to historically small population sizes and bottleneck events. Genetic substructure within any of the native populations was at best weak. Individuals from the admixed population Helge å shared most genetic ancestry with the Båven population (72%). Our results are largely in agreement with the microsatellite study, and stresses the need to protect these isolated populations at the northern edge of the distribution of the species.

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