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.
python-cwl-utils provides python utilities and autogenerated classes for loading and parsing CWL v1.0, CWL v1.1, and CWL v1.2 documents.
This package provides utility functions for manipulating BAM files.
PAIRADISE is a method for detecting allele-specific alternative splicing (ASAS) from RNA-seq data. Unlike conventional approaches that detect ASAS events one sample at a time, PAIRADISE aggregates ASAS signals across multiple individuals in a population. By treating the two alleles of an individual as paired, and multiple individuals sharing a heterozygous SNP as replicates, PAIRADISE formulates ASAS detection as a statistical problem for identifying differential alternative splicing from RNA-seq data with paired replicates.
ParDRe is a parallel tool to remove duplicate genetic sequence reads. Duplicate reads can be seen as identical or nearly identical sequences with some mismatches. This tool lets users avoid the analysis of unnecessary reads, reducing the time of subsequent procedures with the dataset (e.g. assemblies, mappings, etc.). The tool is implemented with MPI in order to exploit the parallel capabilities of multicore clusters. It is faster than multithreaded counterparts (end of 2015) for the same number of cores and, thanks to the message-passing technology, it can be executed on clusters.
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.
Miniasm is a very fast OLC-based de novo assembler for noisy long reads. It takes all-vs-all read self-mappings (typically by minimap) as input and outputs an assembly graph in the GFA format. Different from mainstream assemblers, miniasm does not have a consensus step. It simply concatenates pieces of read sequences to generate the final unitig sequences. Thus the per-base error rate is similar to the raw input reads.
SNAP is a fast and accurate aligner for short DNA reads. It is optimized for modern read lengths of 100 bases or higher, and takes advantage of these reads to align data quickly through a hash-based indexing scheme.
Bio-vcf provides a DSL for processing the VCF format. Record named fields can be queried with regular expressions. Bio-vcf is a new generation VCF parser, filter and converter. Bio-vcf is not only very fast for genome-wide (WGS) data, it also comes with a filtering, evaluation and rewrite language and can output any type of textual data, including VCF header and contents in RDF and JSON.
This package offers a quick and straight-forward way to explore and perform basic analysis of single cell sequencing data coming from droplet sequencing. It has been particularly tailored for Drop-seq.
LAMMPS is a classical molecular dynamics simulator designed to run efficiently on parallel computers. LAMMPS has potentials for solid-state materials (metals, semiconductors), soft matter (biomolecules, polymers), and coarse-grained or mesoscopic systems. It can be used to model atoms or, more generically, as a parallel particle simulator at the atomic, meso, or continuum scale.
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.
This package implements parallel block gzip. For many formats, in particular genomics data formats, data are compressed in fixed-length blocks such that they can be easily indexed based on a (genomic) coordinate order, since typically each block is sorted according to this order. This allows for each block to be individually compressed (deflated), or more importantly, decompressed (inflated), with the latter enabling random retrieval of data in large files (gigabytes to terabytes). pbgzip is not limited to any particular format, but certain features are tailored to genomics data formats when enabled. Parallel decompression is somewhat faster, but the true speedup comes during compression.
This package is a collection of Perl, Python, and R scripts for manipulating 3C/4C/5C/Hi-C data.
This package provides a Python client for BioThings API services.
MACS is an implementation of a ChIP-Seq analysis algorithm for identifying transcript factor binding sites named Model-based Analysis of ChIP-Seq (MACS). MACS captures the influence of genome complexity to evaluate the significance of enriched ChIP regions and it improves the spatial resolution of binding sites through combining the information of both sequencing tag position and orientation.
Sailfish is a tool for genomic transcript quantification from RNA-seq data. It requires a set of target transcripts (either from a reference or de-novo assembly) to quantify. All you need to run sailfish is a fasta file containing your reference transcripts and a (set of) fasta/fastq file(s) containing your reads.
CellTypist is an automated cell type annotation tool for scRNA-seq datasets on the basis of logistic regression classifiers optimised by the stochastic gradient descent algorithm. CellTypist allows for cell prediction using either built-in (with a current focus on immune sub-populations) or custom models, in order to assist in the accurate classification of different cell types and subtypes.
Isolator analyzes RNA-Seq experiments. Isolator has a particular focus on producing stable, consistent estimates. It implements a full hierarchical Bayesian model of an entire RNA-Seq experiment. It saves all the samples generated by the sampler, which can be processed to compute posterior probabilities for arbitrarily complex questions, far beyond the confines of pairwise tests. It aggressively corrects for technical effects, such as random priming bias, GC-bias, 3' bias, and fragmentation effects. Compared to other MCMC approaches, it is exceedingly efficient, though generally slower than modern maximum likelihood approaches.
This package offers Cython bindings and a Python interface for Prodigal. Prodigal is an ORF finder designed for both genomes and metagenomes.
This is an R package for pre-processing of flow and mass cytometry data. This package includes panel editing or renaming for FCS files, bead-based normalization and debarcoding.
The Maxprobes package collects cross-reactive probes of Illumina methylation array 450K and EPIC/850K.
Hclust2 is a handy tool for plotting heat-maps with several useful options to produce high quality figures that can be used in publications.
eXpress is a streaming tool for quantifying the abundances of a set of target sequences from sampled subsequences. Example applications include transcript-level RNA-Seq quantification, allele-specific/haplotype expression analysis (from RNA-Seq), transcription factor binding quantification in ChIP-Seq, and analysis of metagenomic data.
SEEK is a computational gene co-expression search engine. SEEK provides biologists with a way to navigate the massive human expression compendium that now contains thousands of expression datasets. SEEK returns a robust ranking of co-expressed genes in the biological area of interest defined by the user's query genes. It also prioritizes thousands of expression datasets according to the user's query of interest.