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| author | Ricardo Wurmus <rekado@elephly.net> | 2019-06-17 14:39:29 +0200 |
|---|---|---|
| committer | Ricardo Wurmus <rekado@elephly.net> | 2019-06-17 20:22:38 +0200 |
| commit | a6f2ced34b873612e6caca719ed448af3ee92b7e (patch) | |
| tree | 3ce6d32d4e6f37fc12ded98c1464f7ecbd6d2b1e /gnu/packages | |
| parent | bf473f0ca0b218e9a93b00234a8f25ba015b8bd3 (diff) | |
| download | patches-a6f2ced34b873612e6caca719ed448af3ee92b7e.tar patches-a6f2ced34b873612e6caca719ed448af3ee92b7e.tar.gz | |
gnu: Add tbsp.
* gnu/packages/bioinformatics.scm (tbsp): New variable.
Diffstat (limited to 'gnu/packages')
| -rw-r--r-- | gnu/packages/bioinformatics.scm | 37 |
1 files changed, 37 insertions, 0 deletions
diff --git a/gnu/packages/bioinformatics.scm b/gnu/packages/bioinformatics.scm index 90f12f41ec..8002f24110 100644 --- a/gnu/packages/bioinformatics.scm +++ b/gnu/packages/bioinformatics.scm @@ -14756,3 +14756,40 @@ spliced-in} (PSI) values of alternatively-spliced exons that were computed by vast-tools, an RNA-Seq pipeline for alternative splicing analysis. The plots are generated using @code{ggplot2}.") (license license:expat))) + +(define-public tbsp + (let ((commit "ec8fff4410cfb13a677dbbb95cbbc60217e64907") + (revision "1")) + (package + (name "tbsp") + (version (git-version "1.0.0" revision commit)) + (source + (origin + (method git-fetch) + (uri (git-reference + (url "https://github.com/phoenixding/tbsp.git") + (commit commit))) + (sha256 + (base32 + "025ym14x8gbd6hb55lsinqj6f5qzw36i10klgs7ldzxxd7s39ki1")))) + (build-system python-build-system) + (arguments '(#:tests? #f)) ; no tests included + (inputs + `(("python-matplotlib" ,python-matplotlib) + ("python-networkx" ,python-networkx) + ("python-numpy" ,python-numpy) + ("python-pybigwig" ,python-pybigwig) + ("python-biopython" ,python-biopython) + ("python-scikit-learn" ,python-scikit-learn) + ("python-scipy" ,python-scipy))) + (home-page "https://github.com/phoenixding/tbsp/") + (synopsis "SNP-based trajectory inference") + (description + "Several studies focus on the inference of developmental and response +trajectories from single cell RNA-Seq (scRNA-Seq) data. A number of +computational methods, often referred to as pseudo-time ordering, have been +developed for this task. CRISPR has also been used to reconstruct lineage +trees by inserting random mutations. The tbsp package implements an +alternative method to detect significant, cell type specific sequence +mutations from scRNA-Seq data.") + (license license:expat)))) |