About: LoFreq: a sequence-quality aware, ultra-sensitive variant caller for uncovering cell-population heterogeneity from high-throughput sequencing datasets

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About: LoFreq: a sequence-quality aware, ultra-sensitive variant caller for uncovering cell-population heterogeneity from high-throughput sequencing datasets Goto Sponge NotDistinct Permalink

An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	LoFreq: a sequence-quality aware, ultra-sensitive variant caller for uncovering cell-population heterogeneity from high-throughput sequencing datasets
Creator	Hibberd, Martin Bertrand, Denis Nagarajan, Niranjan Petric, Rosemary Wilm, Andreas Ong, Swee Aw, Kim Chuen Khor, Chiea Hui, Grace Poh, Pauline Wong, Chang Yeo, Ting
Source	PMC
abstract	The study of cell-population heterogeneity in a range of biological systems, from viruses to bacterial isolates to tumor samples, has been transformed by recent advances in sequencing throughput. While the high-coverage afforded can be used, in principle, to identify very rare variants in a population, existing ad hoc approaches frequently fail to distinguish true variants from sequencing errors. We report a method (LoFreq) that models sequencing run-specific error rates to accurately call variants occurring in <0.05% of a population. Using simulated and real datasets (viral, bacterial and human), we show that LoFreq has near-perfect specificity, with significantly improved sensitivity compared with existing methods and can efficiently analyze deep Illumina sequencing datasets without resorting to approximations or heuristics. We also present experimental validation for LoFreq on two different platforms (Fluidigm and Sequenom) and its application to call rare somatic variants from exome sequencing datasets for gastric cancer. Source code and executables for LoFreq are freely available at http://sourceforge.net/projects/lofreq/.
has issue date	2012-10-12(xsd:dateTime)
bibo:doi	10.1093/nar/gks918
bibo:pmid	23066108
has license	cc-by-nc
sha1sum (hex)	365b8f727f890a4833a5ab7ca03d443022e7faf2
schema:url	https://doi.org/10.1093/nar/gks918
resource representing a document's title	LoFreq: a sequence-quality aware, ultra-sensitive variant caller for uncovering cell-population heterogeneity from high-throughput sequencing datasets
has PubMed Central identifier	PMC3526318
has PubMed identifier	23066108
schema:publication	Nucleic Acids Res
resource representing a document's body	covid:365b8f727f890a4833a5ab7ca03d443022e7faf2#body_text
is schema:about of	named entity 'ULTRA' named entity 'HETEROGENEITY' named entity 'SEQUENCING RUN' named entity 'TRANSFORMED' named entity 'VIRUSES' named entity 'MODELS' named entity 'NEAR' named entity 'FREQUENTLY' named entity 'REPORT' named entity 'ILLUMINA SEQUENCING' named entity 'SENSITIVITY' named entity 'PRINCIPLE' named entity 'EXOME SEQUENCING' named entity 'SPECIFIC' named entity 'APPLICATION' named entity 'VERY RARE' named entity 'NET' named entity 'HIGH' named entity 'AVAILABLE' named entity 'throughput' named entity 'viruses' named entity 'experimental' named entity 'sourceforge.net' named entity 'caller' named entity 'CELL' named entity 'POPULATION' named entity 'FREELY' named entity 'TO IDENTIFY' named entity 'HEURISTICS' named entity 'HETEROGENEITY' named entity 'QUALITY' named entity 'SEQUENCE' named entity 'VARIANT' named entity 'HTTP' named entity 'DIFFERENT' named entity 'ERROR' named entity 'USED' named entity 'USING' named entity 'SEQUENCING' named entity 'POPULATION' named entity 'UNCOVERING' named entity 'HIGH-THROUGHPUT SEQUENCING' named entity 'SENSITIVE' named entity 'AWARE' named entity 'THROUGHPUT' named entity 'HUMAN' named entity 'TRUE' named entity 'TUMOR' named entity 'GASTRIC CANCER' named entity 'APPROACHES' named entity 'RECENT' named entity 'SAMPLES' named entity 'BIOLOGICAL' named entity 'RATES' named entity 'FAIL' named entity 'PRESENT' named entity 'SOMATIC' named entity 'CELL' named entity 'METHOD' named entity 'COVERAGE' named entity 'IMPROVED' named entity 'SPECIFICITY' named entity 'STUDY' named entity 'RARE' named entity 'COMPARED' named entity 'REAL' named entity 'VALIDATION' named entity 'ITS' named entity 'EXPERIMENTAL' named entity 'METHODS'

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