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| author | Ricardo Wurmus <rekado@elephly.net> | 2024-01-23 21:17:53 +0100 |
|---|---|---|
| committer | Ricardo Wurmus <rekado@elephly.net> | 2024-01-23 21:18:07 +0100 |
| commit | 469405375c84fcfff5822c0506f4ee5832d5f99d (patch) | |
| tree | 02cedc71ed9a92874e1c3d5e18183a6bfc223789 /gnu | |
| parent | 648085dab6c614926c47c6d4f6b8d12d82587724 (diff) | |
| download | guix-469405375c84fcfff5822c0506f4ee5832d5f99d.tar.gz guix-469405375c84fcfff5822c0506f4ee5832d5f99d.zip | |
gnu: Add lsgkm.
* gnu/packages/bioinformatics.scm (lsgkm): New variable.
Change-Id: I0ea35354c7856e7425567cd4ac27ab7fc2ab0d9e
Diffstat (limited to 'gnu')
| -rw-r--r-- | gnu/packages/bioinformatics.scm | 39 |
1 files changed, 39 insertions, 0 deletions
diff --git a/gnu/packages/bioinformatics.scm b/gnu/packages/bioinformatics.scm index 07d0713756..c87e91826c 100644 --- a/gnu/packages/bioinformatics.scm +++ b/gnu/packages/bioinformatics.scm @@ -4728,6 +4728,45 @@ meso, or continuum scale.") files.") (license license:expat))) +(define-public lsgkm + (package + (name "lsgkm") + (version "0.1.1") + (source + (origin + (method git-fetch) + (uri (git-reference + (url "https://github.com/Dongwon-Lee/lsgkm.git") + (commit (string-append "v" version)))) + (file-name (git-file-name name version)) + (sha256 + (base32 + "0b3m94kndvimdfjaf1q2yhmsn7lm5s9v81c5xgfjcp6ig7mh3sa5")))) + (build-system gnu-build-system) + (arguments + (list + #:make-flags '(list "-C" "src") + #:tests? #false ;there are no executable tests + #:phases + #~(modify-phases %standard-phases + (delete 'configure) + (replace 'install + (lambda _ + (let ((bin (string-append #$output "/bin"))) + (for-each (lambda (file) + (install-file file bin)) + '("src/gkmtrain" + "src/gkmpredict")))))))) + (home-page "https://github.com/Dongwon-Lee/lsgkm") + (synopsis "Predict regulatory DNA elements in large-scale data") + (description "gkm-SVM, a sequence-based method for predicting regulatory +DNA elements, is a useful tool for studying gene regulatory mechanisms. +LS-GKM is an effort to improve the method. It offers much better scalability +and provides further advanced gapped k-mer based kernel functions. As a +result, LS-GKM achieves considerably higher accuracy than the original +gkm-SVM.") + (license license:gpl3+))) + (define-public python-pybigwig (package (name "python-pybigwig") |