Estimation of the methylation pattern distribution from deep sequencing data

BMC Bioinformatics

Volumn 16, Issue 1, 2015, Pages

  Lin, Peijie ^a   Forêt, Sylvain ^b   Wilson, Susan R ^a,c   Burden, Conrad J ^a  

^a AUSTRALIAN NATIONAL UNIVERSITY   (Australia)

^b AUSTRALIAN NATIONAL UNIVERSITY   (Australia)

^c UNIVERSITY OF NEW SOUTH WALES   (Australia)

Author keywords

Bisulfite sequencing; DNA methylation; DNA methylation patterns; Epiallele

Indexed keywords

DNA; ERRORS; GENE ENCODING; METHYLATION;

ACCURATE QUANTIFICATIONS; BIOLOGICAL SAMPLES; BISULFITE-SEQUENCING; DNA METHYLATION; DNA METHYLATION PATTERN; EPIALLELE; STATISTICAL MODELING; UNDERLYING DISTRIBUTION;

ALKYLATION;

CYTOSINE; HYDROGEN SULFITE; SULFITE;

ALGORITHM; ANIMAL; BEE; BRAIN; CHEMISTRY; COMPUTER LANGUAGE; DNA METHYLATION; DOCUMENTATION; HIGH THROUGHPUT SEQUENCING; METABOLISM; PHYSIOLOGY; PROCEDURES; STATISTICAL MODEL;

ALGORITHMS; ANIMALS; BEES; BRAIN; CYTOSINE; DNA METHYLATION; DOCUMENTATION; HIGH-THROUGHPUT NUCLEOTIDE SEQUENCING; MODELS, STATISTICAL; PROGRAMMING LANGUAGES; SULFITES;

EID: 84929151861     PISSN: None     EISSN: 14712105     Source Type: Journal    
DOI: 10.1186/s12859-015-0600-6     Document Type: Article

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