This package can be used to normalize cytometry samples when a control sample is taken along in each of the batches. This is done by first identifying multiple clusters/cell types, learning the batch effects from the control samples and applying quantile normalization on all markers of interest.

This package offers a flexible statistical simulator for scRNA-seq data. It can generate data that captures gene correlation. Additionally, it allows for varying the number of cells and sequencing depth.

This package provides tools for dealing with Unique Molecular Identifiers (UMIs) and Random Molecular Tags (RMTs) in genetic sequences. There are six tools: the extract and whitelist commands are used to prepare a fastq containing UMIs +/- cell barcodes for alignment. The remaining commands, group, dedup, and count/count_tab, are used to identify PCR duplicates using the UMIs and perform different levels of analysis depending on the needs of the user.

This library implements a FASTA and a FASTQ parser without relying on a complex dependency tree.

Drop-seq is a technology to enable biologists to analyze RNA expression genome-wide in thousands of individual cells at once. This package provides tools to perform Drop-seq analyses.

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.

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.

This package builds on Seurat's Doheatmap function code to produce a heatmap from a Seurat object with multiple annotation bars.

Biopython is a set of tools for biological computation including parsers for bioinformatics files into Python data structures; interfaces to common bioinformatics programs; a standard sequence class and tools for performing common operations on them; code to perform data classification; code for dealing with alignments; code making it easy to split up parallelizable tasks into separate processes; and more.

NGS is a domain-specific API for accessing reads, alignments and pileups produced from Next Generation Sequencing. The API itself is independent from any particular back-end implementation, and supports use of multiple back-ends simultaneously.

Exonerate is a generic tool for pairwise sequence comparison. It allows the alignment of sequences using a many alignment models, either exhaustive dynamic programming or a variety of heuristics.

CGAT-core is a set of libraries and helper functions used to enable researchers to design and build computational workflows for the analysis of large-scale data-analysis.

Scallop is a reference-based transcript assembler. Scallop features its high accuracy in assembling multi-exon transcripts as well as lowly expressed transcripts.

PLINK is a whole genome association analysis toolset, designed to perform a range of basic, large-scale analyses in a computationally efficient manner. The focus of PLINK is purely on analysis of genotype/phenotype data, so there is no support for steps prior to this (e.g. study design and planning, generating genotype or CNV calls from raw data). Through integration with gPLINK and Haploview, there is some support for the subsequent visualization, annotation and storage of results.

Genrich is a peak-caller for genomic enrichment assays (e.g. ChIP-seq, ATAC-seq). It analyzes alignment files generated following the assay and produces a file detailing peaks of significant enrichment.

Sickle is a tool that trims reads based on quality and length thresholds. It uses sliding windows to detect low-quality bases at the 3'-end and high-quality bases at the 5'-end. Additionally, it discards reads based on the length threshold.

This package is a set of R functions for generating precise figures. This tool helps you to create clean markdown reports about what you just discovered with your analysis script.

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.

Cooler is a support library for a sparse, compressed, binary persistent storage format, called cool, used to store genomic interaction data, such as Hi-C contact matrices.

This package provides utility functions for manipulating BAM files.

Proteinortho is a tool to detect orthologous genes across different species. For doing so, it compares similarities of given gene sequences and clusters them to find significant groups. The algorithm was designed to handle large-scale data and can be applied to hundreds of species at once.

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.

Telomerecat is a tool for estimating the average telomere length (TL) for a paired end, whole genome sequencing (WGS) sample.

Telomerecat is adaptable, accurate and fast. The algorithm accounts for sequencing amplification artifacts, anneouploidy (common in cancer samples) and noise generated by WGS. For a high coverage WGS BAM file of around 100GB telomerecat can produce an estimate in ~1 hour.

This package infers, visualizes and analyzes the cell-cell communication networks from scRNA-seq data.