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This package conducts batch effects removal from a taxa read count table by a conditional quantile regression method. The distributional attributes of microbiome data - zero-inflation and over-dispersion, are simultaneously considered.
Mudata is a Python package for multi-omics data analysis. It is designed to provide functionality to load, process, and store multimodal omics data.
This is a set of functions for processing raw scDam&T-seq data. scDam&T-seq is a method to simultaneously measure protein-DNA interactions and transcription from single cells (Rooijers et al., 2019). It combines a DamID-based method to measure protein-DNA interactions and an adaptation of CEL-Seq to measure transcription. The starting point of the workflow is raw sequencing data and the end result are tables of UMI-unique DamID and CEL-Seq counts.
This package stores motif collections as lists of position frequency matrix (PWMatrixList) objects provided by the TFBSTools package for use in R with packages like motifmatchr or chromVAR.
The package graph implements graph manipulation functions.
NGS is a domain-specific API for accessing reads, alignments and pileups produced from Next Generation Sequencing. The API itself is independent from any particular back-end implementation, and supports use of multiple back-ends simultaneously.
This is a package for normalizing Hi-C contact counts efficiently.
CrossMap is a program for conversion of genome coordinates or annotation files between different genome assemblies. It supports most commonly used file formats including SAM/BAM, Wiggle/BigWig, BED, GFF/GTF, VCF.
IMP's broad goal is to contribute to a comprehensive structural characterization of biomolecules ranging in size and complexity from small peptides to large macromolecular assemblies, by integrating data from diverse biochemical and biophysical experiments. IMP provides a C++ and Python toolbox for solving complex modeling problems, and a number of applications for tackling some common problems in a user-friendly way.
This package is a library to enable flexible and scalable operations on genomic interval dataframes in Python. Bioframe enables access to a rich set of dataframe operations. Working in Python enables rapid visualization and iteration of genomic analyses. The philosophy underlying bioframe is to enable flexible operations. Instead of creating a function for every possible use-case, we encourage users to compose functions to achieve their goals.
hdWGCNA is an R package for performing weighted gene co-expression network analysis in high dimensional -omics such as single-cell RNA-seq or spatial transcriptomics.
RAxML is a tool for phylogenetic analysis and post-analysis of large phylogenies.
Logomaker is a Python package for generating publication-quality sequence logos. Logomaker can generate both standard and highly customized logos illustrating the properties of DNA, RNA, or protein sequences. Logos are rendered as vector graphics embedded within native matplotlib Axes objects, making them easy to style and incorporate into multi-panel figures.
VSEARCH supports DNA sequence searching, clustering, chimera detection, dereplication, pairwise alignment, shuffling, subsampling, sorting and masking. The tool takes advantage of parallelism in the form of SIMD vectorization as well as multiple threads to perform accurate alignments at high speed. VSEARCH uses an optimal global aligner (full dynamic programming Needleman-Wunsch).
TSIS is used for detecting transcript isoform switches in time-series data. Transcript isoform switches occur when a pair of alternatively spliced isoforms reverse the order of their relative expression levels. TSIS characterizes the transcript switch by defining the isoform switch time-points for any pair of transcript isoforms within a gene. In addition, this tool describes the switch using five different features or metrics. Also it filters the results with user’s specifications and visualizes the results using different plots for the user to examine further details of the switches.
Psupertime is supervised pseudotime for single cell RNAseq data. It uses single cell RNAseq data, where the cells have a known ordering. This ordering helps to identify a small number of genes which place cells in that known order. It can be used for discovery of relevant genes, for identification of subpopulations, and characterization of further unknown or differently labelled data.
Ngesh is a Python library and CLI tool for simulating phylogenetic trees and data. It is intended for benchmarking phylogenetic methods, especially in historical linguistics andstemmatology. The generation of stochastic phylogenetic trees also goes by the name simulationmethods for phylogenetic trees, synthetic data generation, or just phylogenetic tree simulation.
The BIOM file format is designed to be a general-use format for representing counts of observations e.g. operational taxonomic units, KEGG orthology groups or lipid types, in one or more biological samples e.g. microbiome samples, genomes, metagenomes.
This library implements an efficient loopless multiset combination generation algorithm which is (approximately) described in "Loopless algorithms for generating permutations, combinations, and other combinatorial configurations.", G. Ehrlich - Journal of the ACM (JACM), 1973. (Algorithm 7.)
This package provides a framework for the analysis and exploration of single-cell chromatin data. The Signac package contains functions for quantifying single-cell chromatin data, computing per-cell quality control metrics, dimension reduction and normalization, visualization, and DNA sequence motif analysis.
HISAT is a fast and sensitive spliced alignment program for mapping RNA-seq reads. In addition to one global FM index that represents a whole genome, HISAT uses a large set of small FM indexes that collectively cover the whole genome. These small indexes (called local indexes) combined with several alignment strategies enable effective alignment of RNA-seq reads, in particular, reads spanning multiple exons.
This package is a Python-based command line interface for processing .bam files with mitochondrial reads and generating high-quality heteroplasmy estimation from sequencing data. The mgatk package places a special emphasis on mitochondrial genotypes generated from single-cell genomics data, primarily mtscATAC-seq, but is generally applicable across other assays.
Genrich is a peak-caller for genomic enrichment assays (e.g. ChIP-seq, ATAC-seq). It analyzes alignment files generated following the assay and produces a file detailing peaks of significant enrichment.
Forester is a collection of Java libraries for phylogenomics and evolutionary biology research. It includes support for reading, writing, and exporting phylogenetic trees.