The pbcopper library provides a suite of data structures, algorithms, and utilities for PacBio C++ applications.

Segemehl is software to map short sequencer reads to reference genomes. Segemehl implements a matching strategy based on enhanced suffix arrays (ESA). It accepts fasta and fastq queries (gzip'ed and bgzip'ed). In addition to the alignment of reads from standard DNA- and RNA-seq protocols, it also allows the mapping of bisulfite converted reads (Lister and Cokus) and implements a split read mapping strategy. The output of segemehl is a SAM or BAM formatted alignment file.

Bloom-filter-based error correction solution for high-throughput sequencing reads (BLESS) uses a single minimum-sized bloom filter is a correction tool for genomic reads produced by Next-generation sequencing (NGS). BLESS produces accurate correction results with much less memory compared with previous solutions and is also able to tolerate a higher false-positive rate. BLESS can extend reads like DNA assemblers to correct errors at the end of reads.

This package implements the custom CRAM codecs used for "EXTERNAL" block types. These consist of two variants of the rANS codec (8-bit and 16-bit renormalisation, with run-length encoding and bit-packing also supported in the latter), a dynamic arithmetic coder, and custom codecs for name/ID compression and quality score compression derived from fqzcomp.

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.

This package implements bindings for zarr store that are compatible with Bioconductor S4 data structures, namely the DataFrame and DelayedArray. This allows Zarr-backed data to be easily used as data frames with arbitrary sets of columns.

This is a package for normalizing Hi-C contact counts efficiently.

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

Millefy is a tool for visualizing read coverage of scRNA-seq(single-cell RNA sequencing) datasets in genomic contexts. By dynamically and automatically reorder single cells based on locus-specific pseudo time, Millefy highlights cell-to-cell heterogeneity in read coverage of scRNA-seq data.

Vembrane simultaneously filters variants based on any INFO or FORMAT field, CHROM, POS, ID, REF, ALT, QUAL, FILTER, and the annotation field ANN. When filtering based on ANN, annotation entries are filtered first. If no annotation entry remains, the entire variant is deleted.

This package provides a toolkit for measuring and comparing ATAC-seq results. It was written to make it easier to spot differences that might be caused by ATAC-seq library prep or sequencing. The main program, ataqv, examines aligned reads and reports some basic metrics.

deMULTIplex is an R package for analyzing single-cell RNA sequencing data generated with the MULTI-seq sample multiplexing method. The package includes software to

1. Convert raw MULTI-seq sample barcode library FASTQs into a sample barcode UMI count matrix, and

2. Classify cell barcodes into sample barcode groups.

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 contains functions for the SCENT algorithm. SCENT uses single-cell multimodal data and links ATAC-seq peaks to their target genes by modeling association between chromatin accessibility and gene expression across individual single cells.

HTSlib is a C library for reading/writing high-throughput sequencing data. It also provides the bgzip, htsfile, and tabix utilities.

This package implements bindings for h5 files that are compatible with Bioconductor S4 data structures, namely the DataFrame and DelayedArray. This allows HDF5-backed data to be easily used as data frames with arbitrary sets of columns.

This is package for including transposable elements in differential enrichment analysis of sequencing datasets. TEtranscripts and TEcount take RNA-seq (and similar data) and annotates reads to both genes and transposable elements. TEtranscripts then performs differential analysis using DESeq2. Note that TEtranscripts and TEcount rely on specially curated GTF files, which are not included due to their size.

The phylo module provides a biojava interface layer to the forester phylogenomics library for constructing phylogenetic trees.

This is a C++ wrapper around the Tabix project which abstracts some of the details of opening and jumping in tabix-indexed files.

This package addresses the challenge of handling large amounts of data that are now routinely generated from DNA sequencing centers. deepTools contains useful modules to process the mapped reads data for multiple quality checks, creating normalized coverage files in standard bedGraph and bigWig file formats, that allow comparison between different files. Finally, using such normalized and standardized files, deepTools can create many publication-ready visualizations to identify enrichments and for functional annotations of the genome.

This package provides an implementation of the BITS (Binary Interval Search) algorithm, an approach to interval set intersection. It is especially suited for the comparison of diverse genomic datasets and the exploration of large datasets of genome intervals (e.g. genes, sequence alignments).

python-cwlformat is a specification and a reference implementation for a very opinionated CWL code formatter. It outputs CWL in a standardized YAML format.

Fxtract extracts sequences from a protein or nucleotide fastx (FASTA or FASTQ) file given a subsequence. It uses a simple substring search for basic tasks but can change to using POSIX regular expressions, PCRE, hash lookups or multi-pattern searching as required. By default fxtract looks in the sequence of each record but can also be told to look in the header, comment or quality sections.

The metacells package implements the improved metacell algorithm for single-cell RNA sequencing (scRNA-seq) data analysis within the scipy framework, and projection algorithm based on it. The original metacell algorithm was implemented in R. The Python package contains various algorithmic improvements and is scalable for larger data sets (millions of cells).