gnu: Add isolator.

* gnu/packages/bioinformatics.scm (isolator): New variable.

Change-Id: I950baca5b6898576f358b3364b1fe541b3333298

gnu/packages/bioinformatics.scm

@@ -7635,6 +7635,49 @@ to measure the reproducibility of findings identified from replicate
 experiments and provide highly stable thresholds based on reproducibility.")
     (license license:gpl2+)))
 
+(define-public isolator
+  (let ((commit "24bafc0a102dce213bfc2b5b9744136ceadaba03")
+        (revision "1"))
+    (package
+      (name "isolator")
+      (version (git-version "0.0.2" revision commit))
+      (source
+       (origin
+         (method git-fetch)
+         (uri (git-reference
+               (url "https://github.com/dcjones/isolator.git")
+               (commit commit)))
+         (file-name (git-file-name name version))
+         (sha256
+          (base32
+           "12mbcfqhiggcjvzizf2ff7b05z31i47njcyzcivpw5j74pfbr3dv"))))
+      (build-system cmake-build-system)
+      (arguments
+       (list
+        #:tests? #f                     ;no check target
+        #:phases
+        '(modify-phases %standard-phases
+           (add-after 'unpack 'fix-std
+             (lambda _
+               (substitute* '("src/summarize.cpp"
+                              "src/shredder.cpp")
+                 (("isnan") "std::isnan")
+                 (("isinf") "std::isinf")))))))
+      (inputs
+       (list boost hdf5 zlib))
+      (home-page "https://github.com/dcjones/isolator")
+      (synopsis "Tools for the analysis of RNA-Seq experiments")
+      (description "Isolator analyzes RNA-Seq experiments.  Isolator has a
+particular focus on producing stable, consistent estimates.  It implements a
+full hierarchical Bayesian model of an entire RNA-Seq experiment.  It saves
+all the samples generated by the sampler, which can be processed to compute
+posterior probabilities for arbitrarily complex questions, far beyond the
+confines of pairwise tests.  It aggressively corrects for technical effects,
+such as random priming bias, GC-bias, 3' bias, and fragmentation effects.
+Compared to other MCMC approaches, it is exceedingly efficient, though
+generally slower than modern maximum likelihood approaches.")
+      (license license:expat))))
+
 (define-public jellyfish
   (package
     (name "jellyfish")