FAN-C provides a pipeline for analysing Hi-C data starting at mapped paired-end sequencing reads.

This package lets you read and write files in Generic Feature Format (GFF) with Biopython integration.

bustools is a program for manipulating BUS files for single cell RNA-Seq datasets. It can be used to error correct barcodes, collapse UMIs, produce gene count or transcript compatibility count matrices, and is useful for many other tasks.

BioJava is a project dedicated to providing a Java framework for processing biological data. It provides analytical and statistical routines, parsers for common file formats, reference implementations of popular algorithms, and allows the manipulation of sequences and 3D structures. The goal of the biojava project is to facilitate rapid application development for bioinformatics.

This package provides the core libraries.

ChIPKernels is an R package for building different string kernels used for DNA Sequence analysis. A dictionary of the desired kernel must be built and this dictionary can be used for determining kernels for DNA Sequences.

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.

Ngesh is a Python library and CLI tool for simulating phylogenetic trees and data. It is intended for benchmarking phylogenetic methods, especially in historical linguistics andstemmatology. The generation of stochastic phylogenetic trees also goes by the name simulationmethods for phylogenetic trees, synthetic data generation, or just phylogenetic tree simulation.

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.

HISAT is a fast and sensitive spliced alignment program for mapping RNA-seq reads. In addition to one global FM index that represents a whole genome, HISAT uses a large set of small FM indexes that collectively cover the whole genome. These small indexes (called local indexes) combined with several alignment strategies enable effective alignment of RNA-seq reads, in particular, reads spanning multiple exons.

ScVelo is a scalable toolkit for RNA velocity analysis in single cells. RNA velocity enables the recovery of directed dynamic information by leveraging splicing kinetics. scVelo generalizes the concept of RNA velocity by relaxing previously made assumptions with a stochastic and a dynamical model that solves the full transcriptional dynamics. It thereby adapts RNA velocity to widely varying specifications such as non-stationary populations.

This is a Python module for analyzing cell-hashing/nucleus-hashing data. It is the demultiplexing module of Pegasus, which is used by Cumulus in the demultiplexing step.

Vcflib provides methods to manipulate and interpret sequence variation as it can be described by VCF. It is both an API for parsing and operating on records of genomic variation as it can be described by the VCF format, and a collection of command-line utilities for executing complex manipulations on VCF files.

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

A tandem repeat in DNA is two or more adjacent, approximate copies of a pattern of nucleotides. Tandem Repeats Finder is a program to locate and display tandem repeats in DNA sequences. In order to use the program, the user submits a sequence in FASTA format. The output consists of two files: a repeat table file and an alignment file. Submitted sequences may be of arbitrary length. Repeats with pattern size in the range from 1 to 2000 bases are detected.

This R package lets you estimate signatures of mutational processes and their activities on mutation count data. Starting from a set of single-nucleotide variants (SNVs), it allows both estimation of the exposure of samples to predefined mutational signatures (including whether the signatures are present at all), and identification of signatures de novo from the mutation counts.

Infernal ("INFERence of RNA ALignment") is a tool for searching DNA sequence databases for RNA structure and sequence similarities. It is an implementation of a special case of profile stochastic context-free grammars called covariance models (CMs). A CM is like a sequence profile, but it scores a combination of sequence consensus and RNA secondary structure consensus, so in many cases, it is more capable of identifying RNA homologs that conserve their secondary structure more than their primary sequence.

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.

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.

ikarus is a stepwise machine learning pipeline that tries to cope with a task of distinguishing tumor cells from normal cells. Leveraging multiple annotated single cell datasets it can be used to define a gene set specific to tumor cells. First, the latter gene set is used to rank cells and then to train a logistic classifier for the robust classification of tumor and normal cells. Finally, sensitivity is increased by propagating the cell labels based on a custom cell-cell network. ikarus is tested on multiple single cell datasets to ascertain that it achieves high sensitivity and specificity in multiple experimental contexts.

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.

This is a package for the discovery of communities in Pore-C concatemers.

This package provides different statistical methods to extract biological activities from omics data within a unified framework.

This package is a rasterization preprocessing framework that aggregates cellular information into spatial pixels to reduce resource requirements for spatial omics data analysis. SEraster reduces the number of points in spatial omics datasets for downstream analysis through a process of rasterization where single cells gene expression or cell-type labels are aggregated into equally sized pixels based on a user-defined resolution. SEraster can be incorporated with other packages to conduct downstream analyses for spatial omics datasets, such as detecting spatially variable genes.

Sickle is a tool that trims reads based on quality and length thresholds. It uses sliding windows to detect low-quality bases at the 3'-end and high-quality bases at the 5'-end. Additionally, it discards reads based on the length threshold.