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Comparing variant calling algorithms for target-exon sequencing in a large sample
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City

Ann Arbor / Council / Ferreira / Indap / New York / Larson / Flygare / Watterson / Washington / /

Company

Target / Affymetrix / HP / AMD / Creative Commons / AT AG CC / Intel / /

Continent

Australia / /

Country

United States / United Kingdom / /

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Facility

University of Michigan Sequencing Core / National Eye Institute / National Human Genome Research Institute / UCL Institute of Ophthalmology / Moorfields Eye Hospital / Health's National Institute / Broad Institute / Alcon Research Institute / University of Michigan / /

IndustryTerm

blade server / imputation algorithms / less complex calling algorithms / variant calling algorithms / computing / /

MarketIndex

IBC singletons with / /

NaturalFeature

Washington Heights / /

Organization

Department of Biostatistics / National Institute of Health / University of Michigan / Department of Health / the University of Michigan / /

Person

Howie B / Peter Vollenweider / Kirsten Herold / Anand Swaroop / Emily Chew / Yang B. Variant / Elaine R Mardis / Gerard Waeber / Dwight Stambolian / Song Y. Genotype / /

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Position

author / Fisher / /

Product

LDaware / /

ProgrammingLanguage

K / T / /

ProvinceOrState

Michigan / South Dakota / Georgia / Massachusetts / Arkansas / /

PublishedMedium

PLoS One / /

Technology

RAM / Bioinformatics / LD-aware algorithm / genotyping / variant calling algorithms / Human Genome / Single Nucleotide Polymorphism / DNA sequencing / imputation algorithms / http / SNP / genotype / recombination / calling algorithm / /

URL

http /

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