BWA-Meth works for single-end reads and for paired-end reads from the directional protocol (most common). It uses the method employed by methylcoder and Bismark of in silico conversion of all C's to T's in both reference and reads. It recovers the original read (needed to tabulate methylation) by attaching it as a comment which BWA appends as a tag to the read. It performs favorably to existing aligners gauged by number of on and off-target reads for a capture method that targets CpG-rich region.

The Filtlong package is a tool for filtering long reads by quality. It can take a set of long reads and produce a smaller, better subset. It uses both read length (longer is better) and read identity (higher is better) when choosing which reads pass the filter.

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.

DelayedArray based image operations.

Bandage is a program for visualising de novo assembly graphs. It allows users to interact with the assembly graphs made by de novo assemblers such as Velvet, SPAdes, MEGAHIT and others. De novo assembly graphs contain not only assembled contigs but also the connections between those contigs, which were previously not easily accessible. Bandage visualises assembly graphs, with connections, using graph layout algorithms. Nodes in the drawn graph, which represent contigs, can be automatically labelled with their ID, length or depth. Users can interact with the graph by moving, labelling and colouring nodes. Sequence information can also be extracted directly from the graph viewer. By displaying connections between contigs, Bandage opens up new possibilities for analysing and improving de novo assemblies that are not possible by looking at contigs alone.

This package provides a simple web interface for the RNA-centric annotation system (RCAS).

HISAT2 is a fast and sensitive alignment program for mapping next-generation sequencing reads (both DNA and RNA) to a population of human genomes (as well as to a single reference genome). In addition to using one global graph FM (GFM) index that represents a population of human genomes, HISAT2 uses a large set of small GFM indexes that collectively cover the whole genome. These small indexes, combined with several alignment strategies, enable rapid and accurate alignment of sequencing reads. This new indexing scheme is called a Hierarchical Graph FM index (HGFM).

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

CoolBox is a toolkit for visual analysis of genomics data. It aims to be highly compatible with the Python ecosystem, easy to use and highly customizable with a well-designed user interface. It can be used in various visualization situations, for example, to produce high-quality genome track plots or fetch common used genomic data files with a Python script or command line, interactively explore genomic data within Jupyter environment or web browser.

Implementation of the Smith-Waterman algorithm.

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.

BamTools provides both a C++ API and a command-line toolkit for handling BAM files.

CENTIPEDE applies a hierarchical Bayesian mixture model to infer regions of the genome that are bound by particular transcription factors. It starts by identifying a set of candidate binding sites, and then aims to classify the sites according to whether each site is bound or not bound by a transcription factor. CENTIPEDE is an unsupervised learning algorithm that discriminates between two different types of motif instances using as much relevant information as possible.

The subread package contains the following tools: subread aligner, a general-purpose read aligner; subjunc aligner: detecting exon-exon junctions and mapping RNA-seq reads; featureCounts: counting mapped reads for genomic features; exactSNP: a SNP caller that discovers SNPs by testing signals against local background noises.

MethylDackel will process a coordinate-sorted and indexed BAM or CRAM file containing some form of BS-seq alignments and extract per-base methylation metrics from them. MethylDackel requires an indexed fasta file containing the reference genome as well.

This package provides a collection of useful functions for working with DNA methylation micro-array data.

HOMER (Hypergeometric Optimization of Motif EnRichment) is a suite of tools for Motif Discovery and next-gen sequencing analysis. It is a collection of command line programs written in Perl and C++. HOMER was primarily written as a de novo motif discovery algorithm and is well suited for finding 8-20 bp motifs in large scale genomics data. HOMER contains many useful tools for analyzing ChIP-Seq, GRO-Seq, RNA-Seq, DNase-Seq, Hi-C and numerous other types of functional genomics sequencing data sets.

Bamnostic is a pure Python Binary Alignment Map (BAM) file parser and random access tool.

Megahit is a fast and memory-efficient NGS assembler. It is optimized for metagenomes, but also works well on generic single genome assembly (small or mammalian size) and single-cell assembly.

This package allows building the hierarchy of domains starting from Hi-C data. Each hierarchical level is identified by a minimum value of physical insulation between neighboring domains.

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 package provides a VCF parser for Python.

Seqtk is a fast and lightweight tool for processing sequences in the FASTA or FASTQ format. It parses both FASTA and FASTQ files which can be optionally compressed by gzip.

This package aims to bring the power and flexibility of AnnData to the R ecosystem, allowing you to effortlessly manipulate and analyze your single-cell data. This package lets you work with backed h5ad and zarr files, directly access various slots (e.g. X, obs, var), or convert the data into SingleCellExperiment and Seurat objects.