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This package provides different statistical methods to extract biological activities from omics data within a unified framework.
Savvy is the official C++ interface for the SAV file format and offers seamless support for BCF and VCF files.
This package is a client implementation of the GA4GH htsget protocol. It provides a simple and reliable way to retrieve genomic data from servers supporting the protocol.
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.
BayesPrism includes deconvolution and embedding learning modules. The deconvolution module models a prior from cell type-specific expression profiles from scRNA-seq to jointly estimate the posterior distribution of cell type composition and cell type-specific gene expression from bulk RNA-seq expression of tumor samples. The embedding learning module uses Expectation-maximization (EM) to approximate the tumor expression using a linear combination of malignant gene programs while conditional on the inferred expression and fraction of non-malignant cells estimated by the deconvolution module.
Infernal ("INFERence of RNA ALignment") is a tool for searching DNA sequence databases for RNA structure and sequence similarities. It is an implementation of a special case of profile stochastic context-free grammars called covariance models (CMs). A CM is like a sequence profile, but it scores a combination of sequence consensus and RNA secondary structure consensus, so in many cases, it is more capable of identifying RNA homologs that conserve their secondary structure more than their primary sequence.
This package provides the ASCAT R package that can be used to infer tumour purity, ploidy and allele-specific copy number profiles.
This package contains a multicore Barnes-Hut implementation of the t-SNE algorithm. The implementation is described here: http://lvdmaaten.github.io/publications/papers/JMLR_2014.pdf.
This package provides basic routines for estimation of gene-specific transcriptional derivatives and visualization of the resulting velocity patterns.
The R package rareMETALS2 is an extension of the R package rareMETALS. It was designed to meta-analyze gene-level association tests for binary trait. While rareMETALS offers a near-complete solution for meta-analysis of gene-level tests for quantitative trait, it does not offer the optimal solution for binary trait. The package rareMETALS2 offers improved features for analyzing gene-level association tests in meta-analyses for binary trait.
This package is a collection of Perl, Python, and R scripts for manipulating 3C/4C/5C/Hi-C data.
This is a collection of functions created and/or curated to aid in the visualization and analysis of single-cell data using R.
Sambamba is a high performance modern robust and fast tool (and library), written in the D programming language, for working with SAM and BAM files. Current parallelised functionality is an important subset of samtools functionality, including view, index, sort, markdup, and depth.
This is the reference implementation of the CWL standards. The CWL open standards are for describing analysis workflows and tools in a way that makes them portable and scalable across a variety of software and hardware environments, from workstations to cluster, cloud, and high performance computing (HPC) environments. CWL is designed to meet the needs of data-intensive science, such as Bioinformatics, Medical Imaging, Astronomy, Physics, and Chemistry. The cwltool is intended to be feature complete and to provide comprehensive validation of CWL files as well as provide other tools related to working with CWL descriptions.
This package computes informative enrichment and quality measures for ChIP-seq/DNase-seq/FAIRE-seq/MNase-seq data. It can also be used to obtain robust estimates of the predominant fragment length or characteristic tag shift values in these assays.
ngshmmalign is a profile HMM aligner for NGS reads designed particularly for small genomes (such as those of RNA viruses like HIV-1 and HCV) that experience substantial biological insertions and deletions.
FLASH (Fast Length Adjustment of SHort reads) is a tool to merge paired-end reads from next-generation sequencing experiments. FLASH is designed to merge pairs of reads when the original DNA fragments are shorter than twice the length of reads. The resulting longer reads can significantly improve genome assemblies. They can also improve transcriptome assembly when FLASH is used to merge RNA-seq data.
Presto is a python toolkit for processing raw reads from high-throughput sequencing of B cell and T cell repertoires.
Centrifuge is a microbial classification engine that enables rapid, accurate and sensitive labeling of reads and quantification of species on desktop computers. The system uses an indexing scheme based on the Burrows-Wheeler transform (BWT) and the Ferragina-Manzini (FM) index, optimized specifically for the metagenomic classification problem. Centrifuge requires a relatively small index (4.7 GB for all complete bacterial and viral genomes plus the human genome) and classifies sequences at very high speed, allowing it to process the millions of reads from a typical high-throughput DNA sequencing run within a few minutes.
This package provides Python bindings for lib2bit to access 2bit files with Python.
The store package provides a number of data store types that are useful for bioinformatic analysis.
InDelFixer is a sensitive aligner for 454, Illumina and PacBio data, employing a full Smith-Waterman alignment against a reference. This Java command line application aligns Next-Generation Sequencing (NGS) and third-generation reads to a set of reference sequences, by a prior fast k-mer matching and removes indels, causing frame shifts. In addition, only a specific region can be considered. An iterative refinement of the alignment can be performed, by alignment against the consensus sequence with wobbles. The output is in SAM format.
pySCENIC is a Python implementation of the SCENIC pipeline (Single-Cell rEgulatory Network Inference and Clustering) which enables biologists to infer transcription factors, gene regulatory networks and cell types from single-cell RNA-seq data.
METAL is a tool for meta-analysis genomewide association scans. METAL can combine either test statistics and standard errors or p-values across studies (taking sample size and direction of effect into account). METAL analysis is a convenient alternative to a direct analysis of merged data from multiple studies. It is especially appropriate when data from the individual studies cannot be analyzed together because of differences in ethnicity, phenotype distribution, gender or constraints in sharing of individual level data imposed. Meta-analysis results in little or no loss of efficiency compared to analysis of a combined dataset including data from all individual studies.