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.

Azimuth utilizes an annotated reference dataset. It automates the processing, analysis, and interpretation. This applies specifically to new single-cell RNA-seq or ATAC-seq experiments. Azimuth leverages a reference-based mapping pipeline that inputs accounts matrix and performs normalization, visualization, cell annotation, and differential expression.

Change-O is a collection of tools for processing the output of V(D)J alignment tools, assigning clonal clusters to immunoglobulin (Ig) sequences, and reconstructing germline sequences.

This package is used for cell type identification in spatial transcriptomics. It also handles cell type-specific differential expression.

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.

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.

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.

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.

Implementation of the Smith-Waterman algorithm.

ParDRe is a parallel tool to remove duplicate genetic sequence reads. Duplicate reads can be seen as identical or nearly identical sequences with some mismatches. This tool lets users avoid the analysis of unnecessary reads, reducing the time of subsequent procedures with the dataset (e.g. assemblies, mappings, etc.). The tool is implemented with MPI in order to exploit the parallel capabilities of multicore clusters. It is faster than multithreaded counterparts (end of 2015) for the same number of cores and, thanks to the message-passing technology, it can be executed on clusters.

Pypairix is a Python module for fast querying on a pairix-indexed bgzipped text file that contains a pair of genomic coordinates per line.

This program searches for and removes remnant adapter sequences from High-Throughput Sequencing (HTS) data and (optionally) trims low quality bases from the 3' end of reads following adapter removal. AdapterRemoval can analyze both single end and paired end data, and can be used to merge overlapping paired-ended reads into (longer) consensus sequences. Additionally, the AdapterRemoval may be used to recover a consensus adapter sequence for paired-ended data, for which this information is not available.

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

This is a Ligand-Receptor inference framework. The framework enables the use of any LR method with any resources.

gkm-SVM, a sequence-based method for predicting regulatory DNA elements, is a useful tool for studying gene regulatory mechanisms. LS-GKM is an effort to improve the method. It offers much better scalability and provides further advanced gapped k-mer based kernel functions. As a result, LS-GKM achieves considerably higher accuracy than the original gkm-SVM.

This package is a library to enable flexible and scalable operations on genomic interval dataframes in Python. Bioframe enables access to a rich set of dataframe operations. Working in Python enables rapid visualization and iteration of genomic analyses. The philosophy underlying bioframe is to enable flexible operations. Instead of creating a function for every possible use-case, we encourage users to compose functions to achieve their goals.

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 provides a converter between .hic files (from juicer) and single-resolution or multi-resolution .cool files (for cooler). Both hic and cool files describe Hi-C contact matrices.

The Spliced Transcripts Alignment to a Reference (STAR) software is based on a previously undescribed RNA-seq alignment algorithm that uses sequential maximum mappable seed search in uncompressed suffix arrays followed by seed clustering and stitching procedure. In addition to unbiased de novo detection of canonical junctions, STAR can discover non-canonical splices and chimeric (fusion) transcripts, and is also capable of mapping full-length RNA sequences.

Isolator analyzes RNA-Seq experiments. Isolator has a particular focus on producing stable, consistent estimates. It implements a full hierarchical Bayesian model of an entire RNA-Seq experiment. It saves all the samples generated by the sampler, which can be processed to compute posterior probabilities for arbitrarily complex questions, far beyond the confines of pairwise tests. It aggressively corrects for technical effects, such as random priming bias, GC-bias, 3' bias, and fragmentation effects. Compared to other MCMC approaches, it is exceedingly efficient, though generally slower than modern maximum likelihood approaches.

Mantis is a space-efficient data structure that can be used to index thousands of raw-read genomics experiments and facilitate large-scale sequence searches on those experiments. Mantis uses counting quotient filters instead of Bloom filters, enabling rapid index builds and queries, small indexes, and exact results, i.e., no false positives or negatives. Furthermore, Mantis is also a colored de Bruijn graph representation, so it supports fast graph traversal and other topological analyses in addition to large-scale sequence-level searches.

WhatsHap is software for phasing genomic variants using DNA sequencing reads, also called read-based phasing or haplotype assembly. It is especially suitable for long reads, but works also well with short reads.

This package provides a convenient interface to minimap2, a fast and accurate C program to align genomic and transcribe nucleotide sequences.

This package provides extra utility functions to perform common tasks in the analysis of omics data, leveraging and enhancing features provided by Bioconductor packages.