~ruther/guix-local

825b3ca76367dc9b084eaf535fd7aafc95b3c8fa — Ricardo Wurmus 2 years ago 3aa60e4
gnu: Add isolator.

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

Change-Id: I950baca5b6898576f358b3364b1fe541b3333298
1 files changed, 43 insertions(+), 0 deletions(-)

M gnu/packages/bioinformatics.scm
M gnu/packages/bioinformatics.scm => gnu/packages/bioinformatics.scm +43 -0
@@ 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")