Simulating the dynamics of targeted capture sequencing with CapSim

Cao, Minh Duc; Ganesamoorthy, Devika; Zhou, Chenxi; Coin, Lachlan

doi:10.1093/bioinformatics/btx691

Cited by 14 publications

(10 citation statements)

References 5 publications

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“…Once genome or transcriptome references are produced or downloaded, the next step is selecting the target loci for bait design. Good starting points for identifying loci with the right amount of genetic variation are the bait design tools MarkerMiner 1.0 (Chamala et al, 2015), BaitFisher (Mayer et al, 2016) and MrBait (Chafin et al, 2018), as well as the simulation package CapSim (Cao et al, 2018). BaitFisher (with its filtering program BaitFilter) and MrBait allow for the design of baits targeting a broad taxonomic spectrum and different enrichment strategies.…”

Section: Designing Bait Setsmentioning

confidence: 99%

A Guide to Carrying Out a Phylogenomic Target Sequence Capture Project

et al. 2020

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High-throughput DNA sequencing techniques enable time-and cost-effective sequencing of large portions of the genome. Instead of sequencing and annotating whole genomes, many phylogenetic studies focus sequencing effort on large sets of pre-selected loci, which further reduces costs and bioinformatic challenges while increasing coverage. One common approach that enriches loci before sequencing is often referred to as target sequence capture. This technique has been shown to be applicable to phylogenetic studies of greatly varying evolutionary depth. Moreover, it has proven to produce powerful, large multi-locus DNA sequence datasets suitable for phylogenetic analyses. However, target capture requires careful considerations, which may greatly affect the success of experiments. Here we provide a simple flowchart for designing phylogenomic target capture experiments. We discuss necessary decisions from the identification of target loci to the final bioinformatic processing of sequence data. We outline challenges and solutions related to the taxonomic scope, sample quality, and available genomic resources of target capture projects. We hope this review will serve as a useful roadmap for designing and carrying out successful phylogenetic target capture studies.

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Section: Designing Bait Setsmentioning

confidence: 99%

A Guide to Carrying Out a Phylogenomic Target Sequence Capture Project

et al. 2020

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“…We used simulated sequencing data to assess the accuracy of our genotyping algorithm. Generation of simulated data is described in Cao et al (2017) [ 24 ]. We first introduced SNPs and small indels to the reference human genome (hg19) to create 4 diploid genomes - Genome1, Genome2, Genome3 and Genome4.…”

Section: Methodsmentioning

confidence: 99%

“…We then introduced repeat variations into these genomes (Additional file 1 : Table S1). We simulated PacBio whole genome sequencing (WGS) data for Genome 2 and we simulated Illumina targeted sequencing data for these 142 loci for all 4 simulated genomes according to Cao et al (2017) [ 24 ]. For simulation of capture sequencing data, we sampled fragments from each genome according to the length distributions observed in real sequencing data (mean 800 bp and standard deviation 100 bp).…”

Section: Methodsmentioning

confidence: 99%

GtTR: Bayesian estimation of absolute tandem repeat copy number using sequence capture and high throughput sequencing

et al. 2018

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BackgroundTandem repeats comprise significant proportion of the human genome including coding and regulatory regions. They are highly prone to repeat number variation and nucleotide mutation due to their repetitive and unstable nature, making them a major source of genomic variation between individuals. Despite recent advances in high throughput sequencing, analysis of tandem repeats in the context of complex diseases is still hindered by technical limitations. We report a novel targeted sequencing approach, which allows simultaneous analysis of hundreds of repeats. We developed a Bayesian algorithm, namely – GtTR - which combines information from a reference long-read dataset with a short read counting approach to genotype tandem repeats at population scale. PCR sizing analysis was used for validation.ResultsWe used a PacBio long-read sequenced sample to generate a reference tandem repeat genotype dataset with on average 13% absolute deviation from PCR sizing results. Using this reference dataset GtTR generated estimates of VNTR copy number with accuracy within 95% high posterior density (HPD) intervals of 68 and 83% for capture sequence data and 200X WGS data respectively, improving to 87 and 94% with use of a PCR reference. We show that the genotype resolution increases as a function of depth, such that the median 95% HPD interval lies within 25, 14, 12 and 8% of the its midpoint copy number value for 30X, 200X WGS, 395X and 800X capture sequence data respectively. We validated nine targets by PCR sizing analysis and genotype estimates from sequencing results correlated well with PCR results.ConclusionsThe novel genotyping approach described here presents a new cost-effective method to explore previously unrecognized class of repeat variation in GWAS studies of complex diseases at the population level. Further improvements in accuracy can be obtained by improving accuracy of the reference dataset.Electronic supplementary materialThe online version of this article (10.1186/s12859-018-2282-3) contains supplementary material, which is available to authorized users.

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“…This can be done by specifying the total number of baits, the number/percentage of baits per category of input file, and if different categories are to be included, for example, known SNPs, genomic regions of particular interest, and masked regions. The tiling can also be specified, as SciTools Web Tools from IDT; or ArrayOligoSelector (Bozdech et al, 2003), and simulation programs (Cao et al, 2018) or external providers (e.g., Arbor Biosciences; Roche), to select the final set of baits. Therefore, by following the short pipeline of supeRbaits, large bait sets for population genomics can be generated with the desired bait properties and placement, in a fast and transparent way.…”

Section: The R-pack Ag E Super Bait S and Its Appli C Ati Onmentioning

confidence: 99%

Fishing for DNA? Designing baits for population genetics in target enrichment experiments: Guidelines, considerations and the new tool supeRbaits

Jiménez‐Mena

Flávio

Henriques

et al. 2022

Molecular Ecology Resources

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Targeted sequencing is an increasingly popular next‐generation sequencing (NGS) approach for studying populations that involves focusing sequencing efforts on specific parts of the genome of a species of interest. Methodologies and tools for designing targeted baits are scarce but in high demand. Here, we present specific guidelines and considerations for designing capture sequencing experiments for population genetics for both neutral genomic regions and regions subject to selection. We describe the bait design process for three diverse fish species: Atlantic salmon, Atlantic cod and tiger shark, which was carried out in our research group, and provide an evaluation of the performance of our approach across both historical and modern samples. The workflow used for designing these three bait sets has been implemented in the R‐package supeRbaits, which encompasses our considerations and guidelines for bait design for the benefit of researchers and practitioners. The supeRbaits R‐package is user‐friendly and versatile. It is written in C++ and implemented in R. supeRbaits and its manual are available from Github: https://github.com/BelenJM/supeRbaits

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Simulating the dynamics of targeted capture sequencing with CapSim

Abstract: Supplementary data are available at Bioinformatics online.

Cited by 14 publications

References 5 publications

A Guide to Carrying Out a Phylogenomic Target Sequence Capture Project

A Guide to Carrying Out a Phylogenomic Target Sequence Capture Project

GtTR: Bayesian estimation of absolute tandem repeat copy number using sequence capture and high throughput sequencing

Fishing for DNA? Designing baits for population genetics in target enrichment experiments: Guidelines, considerations and the new tool supeRbaits

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