Evidence map›Paper›PMID 24831545›Full record

ArticleNucleic acids research2014

Performance comparison of SNP detection tools with illumina exome sequencing data--an assessment using both family pedigree information and sample-matched SNP array data.

Ming Yi, Yongmei Zhao, Li Jia, Mei He, Electron Kebebew, Robert M Stephens

Abstract readEvaluation Study
In one paragraph

Article in Nucleic acids research, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

29 citing papers in PubMed.

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  18. PEMapper and PECaller provide a simplified approach to whole-genome sequencing.Proceedings of the National Academy of Sciences of the United States of America · 2017
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Ming YiAdvanced Biomedical Computing Center, SAIC-Frederick, Inc., Frederick National Laboratory for Cancer Research, Frederick, MD 21702, USA Current address: Cancer Research and Technology Program, Frederick National Laboratory for Cancer Research, Leidos Biomedical Research, Inc. PO Box B, Frederick, MD, 21702. stephensr@mail.nih.gov yiming@mail.nih.gov.
Yongmei ZhaoAdvanced Biomedical Computing Center, SAIC-Frederick, Inc., Frederick National Laboratory for Cancer Research, Frederick, MD 21702, USA.
Li JiaAdvanced Biomedical Computing Center, SAIC-Frederick, Inc., Frederick National Laboratory for Cancer Research, Frederick, MD 21702, USA.
Mei HeEndocrine Oncology Branch, Center for Cancer Research, National Cancer Institute, Bethesda, MD 20892, USA.
Electron KebebewEndocrine Oncology Branch, Center for Cancer Research, National Cancer Institute, Bethesda, MD 20892, USA.
Robert M StephensAdvanced Biomedical Computing Center, SAIC-Frederick, Inc., Frederick National Laboratory for Cancer Research, Frederick, MD 21702, USA Current address: Cancer Research and Technology Program, Frederick National Laboratory for Cancer Research, Leidos Biomedical Research, Inc. PO Box B, Frederick, MD, 21702. stephensr@mail.nih.gov yiming@mail.nih.gov.

Funding

CCR Collaborative Bioinformatics ResourceZICBC011532 · NCI · DIVISION OF BASIC SCIENCES - NCI · PI MALIK, MARIAM · 2013 to 2025
$33.7M
PHS HHS HHSN261200800001E
6 · The paper itself

Abstract

To apply exome-seq-derived variants in the clinical setting, there is an urgent need to identify the best variant caller(s) from a large collection of available options. We have used an Illumina exome-seq dataset as a benchmark, with two validation scenarios--family pedigree information and SNP array data for the same samples, permitting global high-throughput cross-validation, to evaluate the quality of SNP calls derived from several popular variant discovery tools from both the open-source and commercial communities using a set of designated quality metrics. To the best of our knowledge, this is the first large-scale performance comparison of exome-seq variant discovery tools using high-throughput validation with both Mendelian inheritance checking and SNP array data, which allows us to gain insights into the accuracy of SNP calling through such high-throughput validation in an unprecedented way, whereas the previously reported comparison studies have only assessed concordance of these tools without directly assessing the quality of the derived SNPs. More importantly, the main purpose of our study was to establish a reusable procedure that applies high-throughput validation to compare the quality of SNP discovery tools with a focus on exome-seq, which can be used to compare any forthcoming tool(s) of interest.

Indexed as

ExomePolymorphism, Single NucleotideHigh-Throughput Nucleotide SequencingHumansOligonucleotide Array Sequence AnalysisPedigreeSequence Analysis, DNA

Identifiers

PMID24831545
PMCPMC4081058

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.