_            _    _        _         _
      /\ \         /\ \ /\ \     /\_\      / /\
      \_\ \       /  \ \\ \ \   / / /     / /  \
      /\__ \     / /\ \ \\ \ \_/ / /     / / /\ \__
     / /_ \ \   / / /\ \ \\ \___/ /     / / /\ \___\
    / / /\ \ \ / / /  \ \_\\ \ \_/      \ \ \ \/___/
   / / /  \/_// / /   / / / \ \ \        \ \ \
  / / /      / / /   / / /   \ \ \   _    \ \ \
 / / /      / / /___/ / /     \ \ \ /_/\__/ / /
/_/ /      / / /____\/ /       \ \_\\ \/___/ /
\_\/       \/_________/         \/_/ \_____\/

Enter the query into the form above. You can look for specific version of a package by using @ symbol like this: gcc@10.

API method:

GET /api/packages?search=hello&page=1&limit=20

where search is your query, page is a page number and limit is a number of items on a single page. Pagination information (such as a number of pages and etc) is returned in response headers.

If you'd like to join our channel search send a patch to ~whereiseveryone/toys@lists.sr.ht adding your channel as an entry in channels.scm.


r-plsdabatch 0.2.3-1.4aadf3a
Propagated dependencies: r-ggplot2@4.0.3 r-ggpubr@0.6.3 r-gridextra@2.3 r-lmertest@3.2-1 r-mixomics@6.36.0 r-mvtnorm@1.4-1 r-performance@0.17.0 r-rdpack@2.6.6 r-scales@1.4.0
Channel: guix
Location: gnu/packages/bioinformatics.scm (gnu packages bioinformatics)
Home page: https://github.com/EvaYiwenWang/PLSDAbatch
Licenses: GPL 3
Build system: r
Synopsis: PLSDA-batch
Description:

This package provides a new batch effect correction method based on Projection to Latent Structures Discriminant Analysis named “PLSDA-batch” to correct data prior to any downstream analysis. PLSDA-batch estimates latent components related to treatment and batch effects to remove batch variation. The method is multivariate, non-parametric and performs dimension reduction. Combined with centered log ratio transformation for addressing uneven library sizes and compositional structure, PLSDA-batch addresses all characteristics of microbiome data that existing correction methods have ignored so far.

python-harmonypy 0.0.10
Propagated dependencies: python-numpy@2.4.6 python-pandas@3.0.3 python-scikit-learn@1.9.0 python-scipy@1.17.1
Channel: guix
Location: gnu/packages/bioinformatics.scm (gnu packages bioinformatics)
Home page: https://github.com/slowkow/harmonypy
Licenses: GPL 2
Build system: pyproject
Synopsis: Data integration algorithm
Description:

Harmony is an algorithm for integrating multiple high-dimensional datasets with fuzzy k-means and locally linear adjustments.

maffilter 1.3.1
Dependencies: boost@1.89.0 bpp-core@2.4.1 bpp-phyl@2.4.1 bpp-phyl-omics@2.4.1 bpp-seq@2.4.1 bpp-seq-omics@2.4.1 zlib@1.3.1
Channel: guix
Location: gnu/packages/bioinformatics.scm (gnu packages bioinformatics)
Home page: https://jydu.github.io/maffilter/
Licenses: GPL 3+
Build system: cmake
Synopsis: Multiple alignment format file processor
Description:

MafFilter is a program dedicated to the analysis of genome alignments. It parses and manipulates MAF files as well as more simple fasta files. This package can be used to design a pipeline as a series of consecutive filters, each performing a dedicated analysis. Many of the filters are available, from alignment cleaning to phylogeny reconstruction and population genetics analysis. Despite various filtering options and format conversion tools, MafFilter can compute a wide range of statistics (phylogenetic trees, nucleotide diversity, inference of selection, etc.).

orfm 0.7.1
Dependencies: zlib@1.3.1
Channel: guix
Location: gnu/packages/bioinformatics.scm (gnu packages bioinformatics)
Home page: https://github.com/wwood/OrfM
Licenses: LGPL 3+
Build system: gnu
Synopsis: Simple and not slow open reading frame (ORF) caller
Description:

An ORF caller finds stretches of DNA that, when translated, are not interrupted by stop codons. OrfM finds and prints these ORFs.

ruby-bio-kseq 0.0.2
Dependencies: zlib@1.3.1
Channel: guix
Location: gnu/packages/bioinformatics.scm (gnu packages bioinformatics)
Home page: https://github.com/gusevfe/bio-kseq
Licenses: Expat
Build system: ruby
Synopsis: Ruby bindings for the kseq.h FASTA/Q parser
Description:

Bio::Kseq provides ruby bindings to the kseq.h FASTA and FASTQ parsing code. It provides a fast iterator over sequences and their quality scores.

perl-bio-db-hts 3.01
Propagated dependencies: bioperl-minimal@1.7.0 htslib@1.21
Channel: guix
Location: gnu/packages/bioinformatics.scm (gnu packages bioinformatics)
Home page: https://metacpan.org/release/Bio-DB-HTS
Licenses: ASL 2.0
Build system: perl
Synopsis: Perl interface to HTS library for DNA sequencing
Description:

This is a Perl interface to the HTS library for DNA sequencing.

htseq 2.0.9
Propagated dependencies: python-numpy@2.4.6 python-pysam@0.23.3
Channel: guix
Location: gnu/packages/bioinformatics.scm (gnu packages bioinformatics)
Home page: https://github.com/htseq
Licenses: GPL 3+
Build system: pyproject
Synopsis: Framework for analyzing high-throughput sequencing data
Description:

This package provides a framework to process and analyze data from high-throughput sequencing (HTS) assays

python-deeptools 3.5.6
Propagated dependencies: python-matplotlib@3.10.9 python-numpy@2.4.6 python-numpydoc@1.10.0 python-py2bit@0.3.3 python-pybigwig@0.3.25 python-pysam@0.23.3 python-scipy@1.17.1 python-deeptoolsintervals@0.1.9 python-plotly@6.8.0
Channel: guix
Location: gnu/packages/bioinformatics.scm (gnu packages bioinformatics)
Home page: https://pypi.org/project/deepTools/
Licenses: Modified BSD Expat
Build system: pyproject
Synopsis: Useful tools for exploring deep sequencing data
Description:

This package addresses the challenge of handling large amounts of data that are now routinely generated from DNA sequencing centers. deepTools contains useful modules to process the mapped reads data for multiple quality checks, creating normalized coverage files in standard bedGraph and bigWig file formats, that allow comparison between different files. Finally, using such normalized and standardized files, deepTools can create many publication-ready visualizations to identify enrichments and for functional annotations of the genome.

scallop 0.10.5
Dependencies: boost@1.89.0 htslib@1.21
Channel: guix
Location: gnu/packages/bioinformatics.scm (gnu packages bioinformatics)
Home page: https://github.com/Kingsford-Group/scallop
Licenses: Modified BSD
Build system: gnu
Synopsis: Reference-based transcriptome assembler for RNA-seq
Description:

Scallop is a reference-based transcript assembler. Scallop features its high accuracy in assembling multi-exon transcripts as well as lowly expressed transcripts.

prinseq 0.20.4
Dependencies: guile@3.0.9 perl@5.36.0 perl-cairo@1.109 perl-data-dumper@2.183 perl-digest-md5@2.58 perl-getopt-long@2.51 perl-json@4.02 perl-statistics-pca@0.0.1
Channel: guix
Location: gnu/packages/bioinformatics.scm (gnu packages bioinformatics)
Home page: https://prinseq.sourceforge.net/
Licenses: GPL 3+
Build system: gnu
Synopsis: Preprocess sequence data in FASTA or FASTQ formats
Description:

PRINSEQ is a bioinformatics tool to help you preprocess your genomic or metagenomic sequence data in FASTA or FASTQ formats. The tool is written in Perl and can be helpful if you want to filter, reformat, or trim your sequence data. It also generates basic statistics for your sequences.

r-metacell 0.3.41-1.d6a6926
Propagated dependencies: r-cluster@2.1.8.2 r-cowplot@1.2.0 r-data-table@1.18.4 r-dbscan@1.2.5 r-domc@1.3.8 r-dplyr@1.2.1 r-entropy@1.3.2 r-ggplot2@4.0.3 r-graph@1.90.0 r-igraph@2.3.2 r-kernsmooth@2.23-26 r-magrittr@2.0.5 r-matrix@1.7-5 r-matrixstats@1.5.0 r-pdist@1.2.1 r-pheatmap@1.0.13 r-plyr@1.8.9 r-rcolorbrewer@1.1-3 r-rcurl@1.98-1.19 r-rgraphviz@2.56.0 r-slam@0.1-55 r-singlecellexperiment@1.34.0 r-svglite@2.2.2 r-tgconfig@0.1.2-1.15cf199 r-tgstat@2.3.32 r-tgutil@0.1.15-1.db4ff8b r-tidyr@1.3.2 r-umap@0.2.10.0 r-umap@0.2.10.0 r-zoo@1.8-15
Channel: guix
Location: gnu/packages/bioinformatics.scm (gnu packages bioinformatics)
Home page: https://github.com/tanaylab/metacell/
Licenses: Expat
Build system: r
Synopsis: Meta cell analysis for single cell RNA-seq data
Description:

This package facilitates the analysis of single-cell RNA-seq UMI matrices. It does this by computing partitions of a cell similarity graph into small homogeneous groups of cells, which are defined as metacells (MCs). The derived MCs are then used for building different representations of the data, allowing matrix or 2D graph visualization forming a basis for analysis of cell types, subtypes, transcriptional gradients,cell-cycle variation, gene modules and their regulatory models and more.

seqan 3.0.3
Channel: guix
Location: gnu/packages/bioinformatics.scm (gnu packages bioinformatics)
Home page: https://www.seqan.de
Licenses: Modified BSD
Build system: cmake
Synopsis: Library for nucleotide sequence analysis
Description:

SeqAn is a C++ library of efficient algorithms and data structures for the analysis of sequences with the focus on biological data. It contains algorithms and data structures for string representation and their manipulation, online and indexed string search, efficient I/O of bioinformatics file formats, sequence alignment, and more.

fasttree 2.1.10
Channel: guix
Location: gnu/packages/bioinformatics.scm (gnu packages bioinformatics)
Home page: http://www.microbesonline.org/fasttree
Licenses: GPL 2+
Build system: gnu
Synopsis: Infers approximately-maximum-likelihood phylogenetic trees
Description:

FastTree can handle alignments with up to a million of sequences in a reasonable amount of time and memory. For large alignments, FastTree is 100-1,000 times faster than PhyML 3.0 or RAxML 7.

python-gffutils 0.13
Propagated dependencies: python-argcomplete@3.7.2 python-argh@0.31.3 python-biopython@1.87 python-pybedtools@0.12.0 python-pyfaidx@0.9.0.3 python-simplejson@3.20.1
Channel: guix
Location: gnu/packages/bioinformatics.scm (gnu packages bioinformatics)
Home page: https://github.com/daler/gffutils
Licenses: Expat
Build system: pyproject
Synopsis: Tool for manipulation of GFF and GTF files
Description:

python-gffutils is a Python package for working with and manipulating the GFF and GTF format files typically used for genomic annotations. The files are loaded into a SQLite database, allowing much more complex manipulation of hierarchical features (e.g., genes, transcripts, and exons) than is possible with plain-text methods alone.

fastahack 1.0.0
Channel: guix
Location: gnu/packages/bioinformatics.scm (gnu packages bioinformatics)
Home page: https://github.com/ekg/fastahack
Licenses: Expat GPL 2
Build system: gnu
Synopsis: Indexing and sequence extraction from FASTA files
Description:

Fastahack is a small application for indexing and extracting sequences and subsequences from FASTA files. The included library provides a FASTA reader and indexer that can be embedded into applications which would benefit from directly reading subsequences from FASTA files. The library automatically handles index file generation and use.

r-bpcells 0.3.1
Dependencies: hdf5@1.14.6 google-highway@1.3.0 zlib@1.3.1
Propagated dependencies: r-dplyr@1.2.1 r-ggplot2@4.0.3 r-ggrepel@0.9.8 r-hexbin@1.28.5 r-lifecycle@1.0.5 r-magrittr@2.0.5 r-matrix@1.7-5 r-patchwork@1.3.2 r-rcolorbrewer@1.1-3 r-rcpp@1.1.1-1.1 r-rcppeigen@0.3.4.0.2 r-readr@2.2.0 r-rlang@1.2.0 r-scales@1.4.0 r-scattermore@1.2 r-stringr@1.6.0 r-tibble@3.3.1 r-tidyr@1.3.2 r-vctrs@0.7.3 r-genomicranges@1.64.0 r-igraph@2.3.2 r-iranges@2.46.0 r-matrixstats@1.5.0
Channel: guix
Location: gnu/packages/bioinformatics.scm (gnu packages bioinformatics)
Home page: https://github.com/bnprks/BPCells
Licenses: ASL 2.0 Expat
Build system: r
Synopsis: Single cell counts matrices to PCA
Description:

This is a package providing efficient operations for single cell ATAC-seq fragments and RNA counts matrices. It is interoperable with standard file formats, and introduces efficient bit-packed formats that allow large storage savings and increased read speeds.

fit-sne 1.2.1
Dependencies: fftw@3.3.10
Channel: guix
Location: gnu/packages/bioinformatics.scm (gnu packages bioinformatics)
Home page: https://github.com/KlugerLab/FIt-SNE
Licenses: Original BSD Expat ASL 2.0
Build system: gnu
Synopsis: Fast Fourier Transform-accelerated interpolation-based t-SNE
Description:

t-Stochastic Neighborhood Embedding (t-SNE) is a method for dimensionality reduction and visualization of high dimensional datasets. A popular implementation of t-SNE uses the Barnes-Hut algorithm to approximate the gradient at each iteration of gradient descent. This implementation differs in these ways:

  • Instead of approximating the N-body simulation using Barnes-Hut, we interpolate onto an equispaced grid and use FFT to perform the convolution.

  • Instead of computing nearest neighbors using vantage-point trees, we approximate nearest neighbors using the Annoy library. The neighbor lookups are multithreaded to take advantage of machines with multiple cores.

python-mofax 0.3.7-1.e4821fe
Propagated dependencies: python-h5py@3.16.0 python-matplotlib@3.10.9 python-pandas@3.0.3 python-scipy@1.17.1 python-seaborn@0.13.2-0.32088bb
Channel: guix
Location: gnu/packages/bioinformatics.scm (gnu packages bioinformatics)
Home page: https://github.com/bioFAM/mofax
Licenses: Expat
Build system: pyproject
Synopsis: Motif activity finder for transcription factor motif analysis
Description:

MoFax is a Python package for transcription factor motif analysis. It provides convenience functions to load and visualize factor models trained with MOFA+ in Python.

r-markdownreports 4.5.9-1.3ba1103
Propagated dependencies: r-clipr@0.8.1 r-codeandroll2@2.3.6-1.d58e258 r-colorramps@2.3.4 r-devtools@2.5.2 r-gplots@3.3.0 r-markdownhelpers@0.2.0-1.793372d r-rcolorbrewer@1.1-3 r-readwriter@1.5.3-1.91373c4 r-sessioninfo@1.2.4 r-sm@2.2-6.0 r-stringendo@0.6.0-1.15594b1 r-venndiagram@1.8.2 r-vioplot@0.5.1
Channel: guix
Location: gnu/packages/bioinformatics.scm (gnu packages bioinformatics)
Home page: https://github.com/vertesy/MarkdownReports
Licenses: GPL 3
Build system: r
Synopsis: Tool for generating cientific figures and reports
Description:

This is a set of R functions that allows you to generate precise figures. This tool will create clean markdown reports about what you just discovered.

eddylab-squid 1.9g
Dependencies: perl@5.36.0
Channel: guix
Location: gnu/packages/bioinformatics.scm (gnu packages bioinformatics)
Home page: http://eddylab.org/software.html
Licenses: GPL 2
Build system: gnu
Synopsis: C function library for sequence analysis
Description:

SQUID is Sean Eddy's personal library of C functions and utility programs for sequence analysis.

ritornello 2.0.1
Dependencies: samtools@0.1.19 fftw@3.3.10 boost@1.89.0 zlib@1.3.1
Channel: guix
Location: gnu/packages/bioinformatics.scm (gnu packages bioinformatics)
Home page: https://github.com/KlugerLab/Ritornello
Licenses: GPL 3+
Build system: gnu
Synopsis: Control-free peak caller for ChIP-seq data
Description:

Ritornello is a ChIP-seq peak calling algorithm based on signal processing that can accurately call binding events without the need to do a pair total DNA input or IgG control sample. It has been tested for use with narrow binding events such as transcription factor ChIP-seq.

paml 4.9e
Channel: guix
Location: gnu/packages/bioinformatics.scm (gnu packages bioinformatics)
Home page: http://abacus.gene.ucl.ac.uk/software/paml.html
Licenses: GPL 3
Build system: gnu
Synopsis: Phylogentic analysis by maximum likelihood
Description:

PAML (for Phylogentic Analysis by Maximum Likelihood) contains a few programs for model fitting and phylogenetic tree reconstruction using nucleotide or amino-acid sequence data.

python-phenograph 1.5.7
Dependencies: louvain@0.2
Propagated dependencies: python-leidenalg@0.10.2 python-numpy@1.26.4 python-psutil@7.2.2 python-scikit-learn@1.9.0 python-scipy@1.17.1
Channel: guix
Location: gnu/packages/bioinformatics.scm (gnu packages bioinformatics)
Home page: https://github.com/dpeerlab/PhenoGraph.git
Licenses: Expat
Build system: pyproject
Synopsis: Graph-based clustering for high-dimensional single-cell data
Description:

PhenoGraph is a clustering method designed for high-dimensional single-cell data. It works by creating a graph representing phenotypic similarities between cells and then identifying communities in this graph.

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