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Screening the human exome: a comparison of whole genome and whole transcriptome sequencing.

dc.contributor.author Center for HIV/AIDS Vaccine Immunology (CHAVI)
dc.contributor.author Cirulli Rogers, Elizabeth T
dc.contributor.author Ge, Dongliang
dc.contributor.author Goedert, JJ
dc.contributor.author Goldstein, David Benjamin
dc.contributor.author Heinzen, EL
dc.contributor.author Maia, JM
dc.contributor.author Shianna, Kevin V
dc.contributor.author Singh, A
dc.contributor.author Smith, JP
dc.coverage.spatial England
dc.date.accessioned 2011-06-21T17:30:30Z
dc.date.issued 2010
dc.identifier http://www.ncbi.nlm.nih.gov/pubmed/20598109
dc.identifier gb-2010-11-5-r57
dc.identifier.uri https://hdl.handle.net/10161/4395
dc.description.abstract BACKGROUND: There is considerable interest in the development of methods to efficiently identify all coding variants present in large sample sets of humans. There are three approaches possible: whole-genome sequencing, whole-exome sequencing using exon capture methods, and RNA-Seq. While whole-genome sequencing is the most complete, it remains sufficiently expensive that cost effective alternatives are important. RESULTS: Here we provide a systematic exploration of how well RNA-Seq can identify human coding variants by comparing variants identified through high coverage whole-genome sequencing to those identified by high coverage RNA-Seq in the same individual. This comparison allowed us to directly evaluate the sensitivity and specificity of RNA-Seq in identifying coding variants, and to evaluate how key parameters such as the degree of coverage and the expression levels of genes interact to influence performance. We find that although only 40% of exonic variants identified by whole genome sequencing were captured using RNA-Seq; this number rose to 81% when concentrating on genes known to be well-expressed in the source tissue. We also find that a high false positive rate can be problematic when working with RNA-Seq data, especially at higher levels of coverage. CONCLUSIONS: We conclude that as long as a tissue relevant to the trait under study is available and suitable quality control screens are implemented, RNA-Seq is a fast and inexpensive alternative approach for finding coding variants in genes with sufficiently high expression levels.
dc.language eng
dc.language.iso en_US
dc.relation.ispartof Genome Biol
dc.relation.isversionof 10.1186/gb-2010-11-5-r57
dc.subject Base Sequence
dc.subject Databases, Genetic
dc.subject Exons
dc.subject Gene Expression Profiling
dc.subject Gene Expression Regulation
dc.subject Genome, Human
dc.subject Humans
dc.subject Leukocytes, Mononuclear
dc.subject Polymorphism, Single Nucleotide
dc.subject Sequence Alignment
dc.subject Sequence Analysis, DNA
dc.subject Sequence Homology, Nucleic Acid
dc.title Screening the human exome: a comparison of whole genome and whole transcriptome sequencing.
dc.title.alternative
dc.type Journal article
dc.description.version Version of Record
duke.date.pubdate 2010-00-00
duke.description.issue 5
duke.description.volume 11
dc.relation.journal Genome biology
pubs.author-url http://www.ncbi.nlm.nih.gov/pubmed/20598109
pubs.begin-page R57
pubs.issue 5
pubs.organisational-group Basic Science Departments
pubs.organisational-group Duke
pubs.organisational-group Duke Center for Human Genome Variation
pubs.organisational-group Duke Clinical Research Institute
pubs.organisational-group Duke Institute for Brain Sciences
pubs.organisational-group Faculty
pubs.organisational-group Institutes and Centers
pubs.organisational-group Institutes and Provost's Academic Units
pubs.organisational-group Molecular Genetics and Microbiology
pubs.organisational-group School of Medicine
pubs.organisational-group University Institutes and Centers
pubs.publication-status Published
pubs.volume 11
dc.identifier.eissn 1474-760X


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