gnu: Add r-missmethyl.

* gnu/packages/bioconductor.scm (r-missmethyl): New variable.

gnu/packages/bioconductor.scm

@@ -1674,6 +1674,56 @@ in Nature Genetics, January 2018.")
 methylation arrays.")
     (license license:artistic2.0)))
 
+(define-public r-missmethyl
+  (package
+    (name "r-missmethyl")
+    (version "1.32.1")
+    (source (origin
+              (method url-fetch)
+              (uri (bioconductor-uri "missMethyl" version))
+              (sha256
+               (base32
+                "1rrm8m68kgjkrw1wdli5lrwqlavhbm490zgnj5vafzpvx7xajfma"))))
+    (properties `((upstream-name . "missMethyl")))
+    (build-system r-build-system)
+    (propagated-inputs
+     (list r-annotationdbi
+           r-biasedurn
+           r-biobase
+           r-biocgenerics
+           r-genomicranges
+           r-go-db
+           r-illuminahumanmethylation450kanno-ilmn12-hg19
+           r-illuminahumanmethylation450kmanifest
+           r-illuminahumanmethylationepicanno-ilm10b4-hg19
+           r-illuminahumanmethylationepicmanifest
+           r-iranges
+           r-limma
+           r-methylumi
+           r-minfi
+           r-org-hs-eg-db
+           r-ruv
+           r-s4vectors
+           r-statmod
+           r-stringr
+           r-summarizedexperiment))
+    (native-inputs (list r-knitr))
+    (home-page "https://bioconductor.org/packages/missMethyl")
+    (synopsis "Analyzing Illumina HumanMethylation BeadChip data")
+    (description
+     "This is a package for normalization, testing for differential
+variability and differential methylation and gene set testing for data from
+Illumina's Infinium HumanMethylation arrays.  The normalization procedure is
+subset-quantile within-array normalization (SWAN), which allows Infinium I and
+II type probes on a single array to be normalized together.  The test for
+differential variability is based on an empirical Bayes version of Levene's
+test.  Differential methylation testing is performed using RUV, which can
+adjust for systematic errors of unknown origin in high-dimensional data by
+using negative control probes.  Gene ontology analysis is performed by taking
+into account the number of probes per gene on the array, as well as taking
+into account multi-gene associated probes.")
+    (license license:gpl2)))
+
 (define-public r-msdata
   (package
     (name "r-msdata")