This package provides the ASCAT R package that can be used to infer tumour purity, ploidy and allele-specific copy number profiles.

This package adds 3D perspective plotting of points, paths, and line, 3D perspective axes, 3D perspective annotations, and wireframe plots.

Tombo is a suite of tools primarily for the identification of modified nucleotides from nanopore sequencing data. Tombo also provides tools for the analysis and visualization of raw nanopore signal.

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 provides a GFF/GTF file parsing utility providing format conversions, region filtering, FASTA sequence extraction and more.

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.

CLIPper is a tool to define peaks in CLIP-seq datasets.

ikarus is a stepwise machine learning pipeline that tries to cope with a task of distinguishing tumor cells from normal cells. Leveraging multiple annotated single cell datasets it can be used to define a gene set specific to tumor cells. First, the latter gene set is used to rank cells and then to train a logistic classifier for the robust classification of tumor and normal cells. Finally, sensitivity is increased by propagating the cell labels based on a custom cell-cell network. ikarus is tested on multiple single cell datasets to ascertain that it achieves high sensitivity and specificity in multiple experimental contexts.

PhenoGraph is a clustering method designed for high-dimensional single-cell data. It works by creating a graph representing phenotypic similarities between cells and then identifying communities in this graph.

This package contains gatingTemplates, example fcs files and compensation controls for use in CytoExploreR.

Model-based Analysis of Genome-wide CRISPR-Cas9 Knockout (MAGeCK) is a computational tool to identify important genes from the recent genome-scale CRISPR-Cas9 knockout screens technology. Its features include:

1. Simple, easy to use pipeline to screen genes in Genome-wide CRISPR-Cas9 Knockout experiments;

2. High sensitivity and low false discovery rate;

3. Fully utilize the screening data by performing both positive and negative screening in one dataset;

4. Provide statistical evaluation in genes, sgRNAs and pathways;

5. Require as few as 2 samples;

6. Identify cell-type specific targets;

7. A set of visualization features that generate publication standard figures.

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.

Bio++ is a set of C++ libraries for Bioinformatics, including sequence analysis, phylogenetics, molecular evolution and population genetics. This library provides phylogenetics-related modules.

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.

Chromap is a fast method for aligning and preprocessing high throughput chromatin profiles. Typical use cases include:

• trimming sequencing adapters, mapping bulk ATAC-seq or ChIP-seq genomic reads to the human genome and removing duplicates;

• trimming sequencing adapters, mapping single cell ATAC-seq genomic reads to the human genome, correcting barcodes, removing duplicates and performing Tn5 shift;

• split alignment of Hi-C reads against a reference genome.

This package provides a robust, parallelized Python CLI for annotating three prime UTR.

Ngless is a domain-specific language for next-generation sequencing (NGS) data processing.

Circe is a Python package for inferring co-accessibility networks from single-cell ATAC-seq data, using skggm for the graphical lasso and python-scanpy for data processing.

dRep is a Python program for rapidly comparing large numbers of genomes. dRep can also "de-replicate" a genome set by identifying groups of highly similar genomes and choosing the best representative genome for each genome set.

The Maxprobes package collects cross-reactive probes of Illumina methylation array 450K and EPIC/850K.

CD-HIT is a program for clustering and comparing protein or nucleotide sequences. CD-HIT is designed to be fast and handle extremely large databases.

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.

FreeBayes is a Bayesian genetic variant detector designed to find small polymorphisms, specifically SNPs (single-nucleotide polymorphisms), indels (insertions and deletions), MNPs (multi-nucleotide polymorphisms), and complex events (composite insertion and substitution events) smaller than the length of a short-read sequencing alignment.

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.