HapTree: A Novel Bayesian Framework for Single Individual Polyplotyping Using NGS Data

PLoS Computational Biology

Volumn 10, Issue 3, 2014, Pages

  Berger, Emily ^a,b,c   Yorukoglu, Deniz ^b   Peng, Jian ^a,b   Berger, Bonnie ^a,b  

^a MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

^b MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

^c UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ERROR CORRECTION; GENES; GENOME; QUALITY CONTROL;

BAYESIAN FRAMEWORKS; COMPUTATIONAL INVESTIGATION; GENETIC INTERACTION; GENOMICS; HAPLOTYPE PHASING; HAPLOTYPES; ILLUMINA; MAXIMUM-LIKELIHOOD ESTIMATION; NEXT-GENERATION SEQUENCING; PERFORMANCE;

MAXIMUM LIKELIHOOD ESTIMATION;

ACCURACY; ALGORITHM; ANALYTICAL ERROR; ARTICLE; BAYES THEOREM; GENOME; GENOME ANALYSIS; HAPLOTYPE; HAPTREE; ILLUMINA SEQUENCING; MAXIMUM LIKELIHOOD METHOD; MOLECULAR GENETICS; NEXT GENERATION SEQUENCING; POLYPLOIDY; QUALITY CONTROL; SEQUENCE ANALYSIS; TRIPLOIDY;

ALGORITHMS; ALLELES; ANIMALS; BAYES THEOREM; COMPUTATIONAL BIOLOGY; EPIGENESIS, GENETIC; FISHES; GENES, FUNGAL; GENOME; GENOME, HUMAN; GENOTYPE; HAPLOTYPES; HIGH-THROUGHPUT NUCLEOTIDE SEQUENCING; HUMANS; LIKELIHOOD FUNCTIONS; MUTATION; PLANTS; PLOIDIES; POLYMORPHISM, SINGLE NUCLEOTIDE; PROBABILITY; REPRODUCIBILITY OF RESULTS;

EID: 84897413439     PISSN: 1553734X     EISSN: 15537358     Source Type: Journal    
DOI: 10.1371/journal.pcbi.1003502     Document Type: Article

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