MissMethyl: An R package for analyzing data from Illumina's HumanMethylation450 platform

Bioinformatics

Volumn 32, Issue 2, 2016, Pages 286-288

  Phipson, Belinda ^a   Maksimovic, Jovana ^a   Oshlack, Alicia ^a  

^a ROYAL CHILDREN'S HOSPITAL   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

BIOLOGY; CPG ISLAND; DNA METHYLATION; DNA MICROARRAY; HUMAN; HUMAN GENOME; PROCEDURES; SOFTWARE;

COMPUTATIONAL BIOLOGY; CPG ISLANDS; DNA METHYLATION; GENOME, HUMAN; HUMANS; OLIGONUCLEOTIDE ARRAY SEQUENCE ANALYSIS; SOFTWARE;

EID: 84959862869     PISSN: 13674803     EISSN: 14602059     Source Type: Journal    
DOI: 10.1093/bioinformatics/btv560     Document Type: Article

References (11)

1. Akalin, A. et al. (2012) methylKit: A comprehensive R package for the analysis of genome-wide DNA methylation profiles. Genome Biol., 13, R87.
2. Aryee, M. J. et al. (2014) Minfi: A flexible and comprehensive Bioconductor package for the analysis of infinium DNA methylation microarrays. Bioinformatics, 30, 1363-1369.
3. Geeleher, P. et al. (2013) Gene-set analysis is severely biased when applied to genome-wide methylation data. Bioinformatics, 29, 1851-1857.
4. Hansen, K. D. et al. (2011) Increased methylation variation in epigenetic domains across cancer types. Nat. Genet., 43, 768-775.
5. Heyn, H. et al. (2012) Distinct DNA methylomes of newborns and centenarians. Proc. Natl. Acad. Sci. USA, 109, 10522-10527.
6. Law, C. W. et al. (2014) Voom: precision weights unlock linear model analysis tools for RNA-seq read counts. Genome Biol., 15, R29.
7. Maksimovic, J. et al. (2012) SWAN: Subset-quantile within array normalization for illumina infinium HumanMethylation450 BeadChips. Genome Biol., 13, R44.
8. Maksimovic, J. et al. (2015) Removing unwanted variation in a differential methylation analysis of illumina humanmethylation450 array data. Nucleic Acids Res., 43, e106.
9. Phipson, B. And Oshlack, A. (2014) DiffVar: A new method for detecting differential variability with application to methylation in cancer and aging. Genome Biol., 15, 465.
10. Ritchie, M. E. et al. (2015) Limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res., 43, e47.
11. Young, M. D. et al. (2010) Gene ontology analysis for RNA-seq: Accounting for selection bias. Genome Biol., 11, R14.