Using false discovery rates to benchmark SNP-callers in next-generation sequencing projects

Rhys A Farrer; Daniel A Henk; Dan MacLean; David J Studholme; Matthew C Fisher

doi:10.1038/srep01512

Using false discovery rates to benchmark SNP-callers in next-generation sequencing projects

Rhys A Farrer
, Daniel A Henk
, Dan MacLean
, David J Studholme
, Matthew C Fisher

Imperial College London
The Sainsbury Laboratory
University of Exeter

Research output: Contribution to journal › Article › peer-review

33 Citations (SciVal)

266 Downloads (Pure)

Abstract

Sequence alignments form the basis for many comparative and population genomic studies. Alignment
tools provide a range of accuracies dependent on the divergence between the sequences and the alignment
methods. Despite widespread use, there is no standard method for assessing the accuracy of a dataset and
alignment strategy after resequencing. We present a framework and tool for determining the overall
accuracies of an input read dataset, alignment and SNP-calling method providing an isolate in that dataset
has a corresponding, or closely related reference sequence available. In addition to this tool for comparing
FalseDiscoveryRates(FDR),weincludeamethodfordetermininghomozygousandheterozygouspositions
from an alignment using binomial probabilities for an expected error rate. We benchmark this method
against other SNP callers using our FDR method with three fungal genomes, finding that it was able achieve
a high level of accuracy. These tools are available at http://cfdr.sourc

Original language	English
Article number	1512
Journal	Scientific Reports
Volume	3
DOIs	https://doi.org/10.1038/srep01512
Publication status	Published - 21 Mar 2013

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-nd/3.0/
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title = "Using false discovery rates to benchmark SNP-callers in next-generation sequencing projects",

abstract = "Sequence alignments form the basis for many comparative and population genomic studies. Alignment tools provide a range of accuracies dependent on the divergence between the sequences and the alignment methods. Despite widespread use, there is no standard method for assessing the accuracy of a dataset and alignment strategy after resequencing. We present a framework and tool for determining the overall accuracies of an input read dataset, alignment and SNP-calling method providing an isolate in that dataset has a corresponding, or closely related reference sequence available. In addition to this tool for comparing FalseDiscoveryRates(FDR),weincludeamethodfordetermininghomozygousandheterozygouspositions from an alignment using binomial probabilities for an expected error rate. We benchmark this method against other SNP callers using our FDR method with three fungal genomes, finding that it was able achieve a high level of accuracy. These tools are available at http://cfdr.sourc",

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AU - Farrer, Rhys A

AU - Henk, Daniel A

AU - MacLean, Dan

AU - Studholme, David J

AU - Fisher, Matthew C

PY - 2013/3/21

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N2 - Sequence alignments form the basis for many comparative and population genomic studies. Alignment tools provide a range of accuracies dependent on the divergence between the sequences and the alignment methods. Despite widespread use, there is no standard method for assessing the accuracy of a dataset and alignment strategy after resequencing. We present a framework and tool for determining the overall accuracies of an input read dataset, alignment and SNP-calling method providing an isolate in that dataset has a corresponding, or closely related reference sequence available. In addition to this tool for comparing FalseDiscoveryRates(FDR),weincludeamethodfordetermininghomozygousandheterozygouspositions from an alignment using binomial probabilities for an expected error rate. We benchmark this method against other SNP callers using our FDR method with three fungal genomes, finding that it was able achieve a high level of accuracy. These tools are available at http://cfdr.sourc

AB - Sequence alignments form the basis for many comparative and population genomic studies. Alignment tools provide a range of accuracies dependent on the divergence between the sequences and the alignment methods. Despite widespread use, there is no standard method for assessing the accuracy of a dataset and alignment strategy after resequencing. We present a framework and tool for determining the overall accuracies of an input read dataset, alignment and SNP-calling method providing an isolate in that dataset has a corresponding, or closely related reference sequence available. In addition to this tool for comparing FalseDiscoveryRates(FDR),weincludeamethodfordetermininghomozygousandheterozygouspositions from an alignment using binomial probabilities for an expected error rate. We benchmark this method against other SNP callers using our FDR method with three fungal genomes, finding that it was able achieve a high level of accuracy. These tools are available at http://cfdr.sourc

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Using false discovery rates to benchmark SNP-callers in next-generation sequencing projects

Abstract

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