MAGIC is an interactive tool to impute missing values in single-cell sequencing data and to restore the structure of the data. It also provides data pre-processing functionality such as dimensionality reduction and gene expression visualization.

This package provides a deconvolution based on Single Nucleotide Position (SNP) for multiplexed scRNA-seq data. The name vireo stand for Variational Inference for Reconstructing Ensemble Origin by expressed SNPs in multiplexed scRNA-seq data and follows the clone identification from single-cell data named cardelino.

This package provides a library and collection of scripts to work with Illumina paired-end data (for CASAVA 1.8+).

This package provides a tool for identifying and removing doublets in single-cell RNA-seq data.

This program compares version strings. It intends to be a replacement for strverscmp.

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.

python-cwl-utils provides python utilities and autogenerated classes for loading and parsing CWL v1.0, CWL v1.1, and CWL v1.2 documents.

DIAMOND is a BLAST-compatible local aligner for mapping protein and translated DNA query sequences against a protein reference database (BLASTP and BLASTX alignment mode). The speedup over BLAST is up to 20,000 on short reads at a typical sensitivity of 90-99% relative to BLAST depending on the data and settings.

Sleuth is a program for differential analysis of RNA-Seq data. It makes use of quantification uncertainty estimates obtained via Kallisto for accurate differential analysis of isoforms or genes, allows testing in the context of experiments with complex designs, and supports interactive exploratory data analysis via sleuth live.

QTLtools is a tool set for molecular QTL discovery and analysis. It allows going from the raw genetic sequence data to collection of molecular Quantitative Trait Loci (QTLs) in few easy-to-perform steps.

This package contains data used by pagoda2. The data within this package are the 3000 bone marrow cells used for vignettes.

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.

This package provides a toolkit for measuring and comparing ATAC-seq results. It was written to make it easier to spot differences that might be caused by ATAC-seq library prep or sequencing. The main program, ataqv, examines aligned reads and reports some basic metrics.

PyEGA3 is a tool for viewing and downloading files from authorized EGA datasets. It uses the EGA data API and has several key features:

• Files are transferred over secure https connections and received unencrypted, so no need for decryption after download.

• Downloads resume from where they left off in the event that the connection is interrupted.

• Supports file segmenting and parallelized download of segments, improving overall performance.

• After download completes, file integrity is verified using checksums.

• Implements the GA4GH-compliant htsget protocol for download of genomic ranges for data files with accompanying index files.

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.

Cyvcf2 is a Cython wrapper around htslib built for fast parsing of Variant Call Format (VCF) files.

This tool is for building Generalized Additive Models in Python. It emphasizes modularity and performance. The API will be immediately familiar to anyone with experience of scikit-learn or scipy.

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.

MultiQC is a tool to aggregate bioinformatics results across many samples into a single report. It contains modules for a large number of common bioinformatics tools.

This package provides string parsing functionalities for generating plotnames, filenames and paths.

Ngs-bits (Next-Generation Sequencing) is collection of short-read and long-read sequencing tools for diagnostics.

Aragorn identifies transfer RNA, mitochondrial RNA and transfer-messenger RNA from nucleotide sequences, based on homology to known tRNA consensus sequences and RNA structure. It also outputs the secondary structure of the predicted RNA.

HTSlib is a C library for reading/writing high-throughput sequencing data. It also provides the bgzip, htsfile, and tabix utilities.

WebLogo is a web based application designed to make the generation of sequence logos as easy and painless as possible.

WebLogo can create output in several common graphics' formats, including the bitmap formats GIF and PNG, suitable for on-screen display, and the vector formats EPS and PDF, more suitable for printing, publication, and further editing. Additional graphics options include bitmap resolution, titles, optional axis, and axis labels, antialiasing, error bars, and alternative symbol formats.

A sequence logo is a graphical representation of an amino acid or nucleic acid multiple sequence alignment. Each logo consists of stacks of symbols, one stack for each position in the sequence. The overall height of the stack indicates the sequence conservation at that position, while the height of symbols within the stack indicates the relative frequency of each amino or nucleic acid at that position. The width of the stack is proportional to the fraction of valid symbols in that position.