This package provides a toolbox to process, analyze and visualize spatial single-cell expression data.

This package detects naive associations between omics features and metadata in cross-sectional data-sets using non-parametric tests. In a second step, confounding effects between metadata associated to the same omics feature are detected and labeled using nested post-hoc model comparison tests. The generated output can be graphically summarized using the built-in plotting function.

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.

Prodigal runs smoothly on finished genomes, draft genomes, and metagenomes, providing gene predictions in GFF3, Genbank, or Sequin table format. It runs quickly, in an unsupervised fashion, handles gaps, handles partial genes, and identifies translation initiation sites.

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.

The NCBI-VDB library implements a highly compressed columnar data warehousing engine that is most often used to store genetic information. Databases are stored in a portable image within the file system, and can be accessed/downloaded on demand across HTTP.

t-Stochastic Neighborhood Embedding (t-SNE) is a highly successful 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 package is a Cython wrapper for FIt-SNE.

EMBOSS is the "European Molecular Biology Open Software Suite". EMBOSS is an analysis package specially developed for the needs of the molecular biology (e.g. EMBnet) user community. The software automatically copes with data in a variety of formats and even allows transparent retrieval of sequence data from the web. It also provides a number of libraries for the development of software in the field of molecular biology. EMBOSS also integrates a range of currently available packages and tools for sequence analysis into a seamless whole.

SlamDunk is a fully automated tool for automated, robust, scalable and reproducible SLAMseq data analysis. Diagnostic plotting features and a MultiQC plugin will make your SLAMseq data ready for immediate QA and interpretation.

This package provides a Variant Effect Predictor, which predicts the functional effects of genomic variants. It also provides Haplosaurus, which uses phased genotype data to predict whole-transcript haplotype sequences, and Variant Recoder, which translates between different variant encodings.

Picard is a set of Java command line tools for manipulating high-throughput sequencing (HTS) data and formats. Picard is implemented using the HTSJDK Java library to support accessing file formats that are commonly used for high-throughput sequencing data such as SAM, BAM, CRAM and VCF.

gkm-SVM, a sequence-based method for predicting regulatory DNA elements, is a useful tool for studying gene regulatory mechanisms. LS-GKM is an effort to improve the method. It offers much better scalability and provides further advanced gapped k-mer based kernel functions. As a result, LS-GKM achieves considerably higher accuracy than the original gkm-SVM.

Kraken is a taxonomic sequence classifier that assigns taxonomic labels to DNA sequences. Kraken examines the k-mers within a query sequence and uses the information within those k-mers to query a database. That database maps k-mers to the lowest common ancestor (LCA) of all genomes known to contain a given k-mer.

This package contains the Battenberg R package for subclonal copy number estimation, as described by Nik-Zainal et al.

ReadWriter is a set of R functions to read and write files conveniently.

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.

Savvy is the official C++ interface for the SAV file format and offers seamless support for BCF and VCF files.

FastQC aims to provide a simple way to do some quality control checks on raw sequence data coming from high throughput sequencing pipelines. It provides a modular set of analyses which you can use to give a quick impression of whether your data has any problems of which you should be aware before doing any further analysis.

The main functions of FastQC are:

• Import of data from BAM, SAM or FastQ files (any variant);

• Providing a quick overview to tell you in which areas there may be problems;

• Summary graphs and tables to quickly assess your data;

• Export of results to an HTML based permanent report;

• Offline operation to allow automated generation of reports without running the interactive application.

Collectively, the bedtools utilities are a swiss-army knife of tools for a wide-range of genomics analysis tasks. The most widely-used tools enable genome arithmetic: that is, set theory on the genome. For example, bedtools allows one to intersect, merge, count, complement, and shuffle genomic intervals from multiple files in widely-used genomic file formats such as BAM, BED, GFF/GTF, VCF.

This tool detects batch effects in high-dimensional data based on chi^2-test.

Pybiomart provides a simple pythonic interface to biomart.

Pyahocorasick is a fast, memory-efficient library for multi-pattern string search. This means that you can find multiple key strings occurrences at once in some input text.

Screed parses FASTA and FASTQ files and generates databases. Values such as sequence name, sequence description, sequence quality and the sequence itself can be retrieved from these databases.

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.