wfmash is a DNA sequence read mapper based on mash distances and the wavefront alignment algorithm. It is a fork of MashMap that implements base-level alignment via the wflign tiled wavefront global alignment algorithm. It completes MashMap with a high-performance alignment module capable of computing base-level alignments for very large sequences.

BitMapperBS is memory-efficient aligner that is designed for whole-genome bisulfite sequencing (WGBS) reads from directional protocol.

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

This package provides a VCF parser for Python.

Pando leverages multi-modal single-cell measurements to infer gene regulatory networks using a flexible linear model-based framework. By modeling the relationship between TF-binding site pairs with the expression of target genes, Pando simultaneously infers gene modules and sets of regulatory regions for each transcription factor.

Pysam is a Python module for reading and manipulating files in the SAM/BAM format. Pysam is a lightweight wrapper of the SAMtools C API. It also includes an interface for tabix.

This package contains a multicore Barnes-Hut implementation of the t-SNE algorithm. The implementation is described here: http://lvdmaaten.github.io/publications/papers/JMLR_2014.pdf.

BWA is a software package for mapping low-divergent sequences against a large reference genome, such as the human genome. It consists of three algorithms: BWA-backtrack, BWA-SW and BWA-MEM. The first algorithm is designed for Illumina sequence reads up to 100bp, while the rest two for longer sequences ranged from 70bp to 1Mbp. BWA-MEM and BWA-SW share similar features such as long-read support and split alignment, but BWA-MEM, which is the latest, is generally recommended for high-quality queries as it is faster and more accurate. BWA-MEM also has better performance than BWA-backtrack for 70-100bp Illumina reads.

This package stores information and scripts to work with, or load various different spatial datasets that can be used with the Giotto Suite workflow. It also contains example mini Giotto subobjects.

Mosaicatcher counts Strand-seq reads and classifies strand states of each chromosome in each cell using a Hidden Markov Model.

JAMM is a peak finder for next generation sequencing datasets (ChIP-Seq, ATAC-Seq, DNase-Seq, etc.) that can integrate replicates and assign peak boundaries accurately. JAMM is applicable to both broad and narrow datasets.

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.

Ribotaper is a method for defining translated open reading frames (ORFs) using ribosome profiling (ribo-seq) data. This package provides the Ribotaper pipeline.

PAML (for Phylogentic Analysis by Maximum Likelihood) contains a few programs for model fitting and phylogenetic tree reconstruction using nucleotide or amino-acid sequence data.

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.

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.

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 set of R functions to parse markdown and other generic helpers.

CMSeq is a set of commands to provide an interface to .bam files for coverage and sequence consensus.

dnaio is a Python library for fast parsing of FASTQ and also FASTA files. The code was previously part of the cutadapt tool.

Flexbar preprocesses high-throughput nucleotide sequencing data efficiently. It demultiplexes barcoded runs and removes adapter sequences. Moreover, trimming and filtering features are provided. Flexbar increases read mapping rates and improves genome and transcriptome assemblies. It supports next-generation sequencing data in fasta/q and csfasta/q format from Illumina, Roche 454, and the SOLiD platform.

Kallisto is a program for quantifying abundances of transcripts from RNA-Seq data, or more generally of target sequences using high-throughput sequencing reads. It is based on the novel idea of pseudoalignment for rapidly determining the compatibility of reads with targets, without the need for alignment. Pseudoalignment of reads preserves the key information needed for quantification, and kallisto is therefore not only fast, but also as accurate as existing quantification tools.

This library contains the genomics components of the Bio++ phylogenetics library. It is part of the Bio++ project.

Cell2cell is a Python library for cell communication analysis. This is a method to calculate, visualize and analyze communication between cell types. Cell2cell is suitable for single-cell RNA sequencing (scRNA-seq) data.