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branch master updated: gnu: Add lsgkm.
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guix-commits |
Subject: |
branch master updated: gnu: Add lsgkm. |
Date: |
Tue, 23 Jan 2024 15:18:30 -0500 |
This is an automated email from the git hooks/post-receive script.
rekado pushed a commit to branch master
in repository guix.
The following commit(s) were added to refs/heads/master by this push:
new 469405375c gnu: Add lsgkm.
469405375c is described below
commit 469405375c84fcfff5822c0506f4ee5832d5f99d
Author: Ricardo Wurmus <rekado@elephly.net>
AuthorDate: Tue Jan 23 21:17:53 2024 +0100
gnu: Add lsgkm.
* gnu/packages/bioinformatics.scm (lsgkm): New variable.
Change-Id: I0ea35354c7856e7425567cd4ac27ab7fc2ab0d9e
---
gnu/packages/bioinformatics.scm | 39 +++++++++++++++++++++++++++++++++++++++
1 file changed, 39 insertions(+)
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")
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