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

This package provides version 1.12 of the HTSlib C library for high-throughput sequence analysis. The package is primarily useful to developers of other R packages who wish to make use of HTSlib.

HTSJDK is an implementation of a unified Java library for accessing common file formats, such as SAM and VCF, used for high-throughput sequencing (HTS) data. There are also an number of useful utilities for manipulating HTS data.

Collectively, the bedtools utilities are a swiss-army knife of tools for a wide-range of genomics analysis tasks. The most widely-used tools enable genome arithmetic: that is, set theory on the genome. For example, bedtools allows one to intersect, merge, count, complement, and shuffle genomic intervals from multiple files in widely-used genomic file formats such as BAM, BED, GFF/GTF, VCF.

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.

Python-airr provides a library by the AIRR community to for describing, reporting, storing, and sharing adaptive immune receptor repertoire (AIRR) data, such as sequences of antibodies and T cell receptors (TCRs).

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.

LIANA provides a number of methods and resource for ligand-receptor interaction inference from scRNA-seq data.

genomepy is designed to provide a simple and straightforward way to download and use genomic data. This includes

1. searching available data,

2. showing the available metadata,

3. automatically downloading, preprocessing and matching data, and

4. generating optional aligner indexes.

All with sensible, yet controllable defaults.

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.

Logomaker is a Python package for generating publication-quality sequence logos. Logomaker can generate both standard and highly customized logos illustrating the properties of DNA, RNA, or protein sequences. Logos are rendered as vector graphics embedded within native matplotlib Axes objects, making them easy to style and incorporate into multi-panel figures.

BWA-PSSM is a probabilistic short genomic sequence read aligner based on the use of position specific scoring matrices (PSSM). Like many of the existing aligners it is fast and sensitive. Unlike most other aligners, however, it is also adaptible in the sense that one can direct the alignment based on known biases within the data set. It is coded as a modification of the original BWA alignment program and shares the genome index structure as well as many of the command line options.

RSEM is a software package for estimating gene and isoform expression levels from RNA-Seq data. The RSEM package provides a user-friendly interface, supports threads for parallel computation of the EM algorithm, single-end and paired-end read data, quality scores, variable-length reads and RSPD estimation. In addition, it provides posterior mean and 95% credibility interval estimates for expression levels. For visualization, it can generate BAM and Wiggle files in both transcript-coordinate and genomic-coordinate.

Velvet is a de novo genomic assembler specially designed for short read sequencing technologies, such as Solexa or 454. Velvet currently takes in short read sequences, removes errors then produces high quality unique contigs. It then uses paired read information, if available, to retrieve the repeated areas between contigs.

This package provides an automated pipeline for spatial mapping of unique transcripts.

This program compares version strings. It intends to be a replacement for strverscmp.

The WiggleTools package allows genomewide data files to be manipulated as numerical functions, equipped with all the standard functional analysis operators (sum, product, product by a scalar, comparators), and derived statistics (mean, median, variance, stddev, t-test, Wilcoxon's rank sum test, etc).

Parabam is a tool for processing sequencing files in parallel. It uses Python's native multiprocessing framework to apply a user defined rule on an input file.

libmaus2 is a collection of data structures and algorithms. It contains:

• I/O classes (single byte and UTF-8);

• bitio classes (input, output and various forms of bit level manipulation);

• text indexing classes (suffix and LCP array, fulltext and minute (FM), etc.);

• BAM sequence alignment files input/output (simple and collating); and many lower level support classes.

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.

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.

Straw is library which allows rapid streaming of contact data from .hic files. This package provides Python bindings.

dRep is a Python program for rapidly comparing large numbers of genomes. dRep can also "de-replicate" a genome set by identifying groups of highly similar genomes and choosing the best representative genome for each genome set.

Anglemania extracts genes from multi-batch scRNA-seq experiments for downstream dataset integration. It improves conventional usage of highly-variable genes for integration tasks.