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.

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.

BBKNN is a batch effect removal tool that can be directly used in the Scanpy workflow. It serves as an alternative to scanpy.api.pp.neighbors(), with both functions creating a neighbour graph for subsequent use in clustering, pseudotime and UMAP visualisation. If technical artifacts are present in the data, they will make it challenging to link corresponding cell types across different batches. BBKNN actively combats this effect by splitting your data into batches and finding a smaller number of neighbours for each cell within each of the groups. This helps create connections between analogous cells in different batches without altering the counts or PCA space.

The wavefront alignment (WFA) algorithm is an exact gap-affine algorithm that takes advantage of homologous regions between the sequences to accelerate the alignment process.

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 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 implements an algorithm which increases the number of simultaneously measurable markers and in this way helps with study of the immune responses. Thus, the present algorithm, named CytoBackBone, allows combining phenotypic information of cells from different cytometric profiles obtained from different cytometry panels. This computational approach is based on the principle that each cell has its own phenotypic and functional characteristics that can be used as an identification card. CytoBackBone uses a set of predefined markers, that we call the backbone, to define this identification card. The phenotypic information of cells with similar identification cards in the different cytometric profiles is then merged.

The data within this package is a panel of four samples, each with 3000 cells. There are two samples which are bone marrow (BM), and two samples which are cord blood (CB).

The NCBI-VDB library implements a highly compressed columnar data warehousing engine that is most often used to store genetic information. Databases are stored in a portable image within the file system, and can be accessed/downloaded on demand across HTTP.

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

python-scanrbp is a Python package that provides the scanRBP tool that loads RNA-protein binding motif PWM and computes the log-odds scores for all the loaded RBPs across a given genomic sequence and draws a heatmap of the scores.

This package implements methods to project single-cell RNA-seq data onto a reference atlas, enabling interpretation of unknown cell transcriptomic states in the the context of known, reference states.

This package provides string parsing functionalities for generating plotnames, filenames and paths.

This package conducts batch effects removal from a taxa read count table by a conditional quantile regression method. The distributional attributes of microbiome data - zero-inflation and over-dispersion, are simultaneously considered.

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.

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.

This package contains some tools for processing BAM files including:

• bamsormadup: parallel sorting and duplicate marking

• bamcollate2: reads BAM and writes BAM reordered such that alignment or collated by query name

• bammarkduplicates: reads BAM and writes BAM with duplicate alignments marked using the BAM flags field

• bammaskflags: reads BAM and writes BAM while masking (removing) bits from the flags column

• bamrecompress: reads BAM and writes BAM with a defined compression setting. This tool is capable of multi-threading.

• bamsort: reads BAM and writes BAM resorted by coordinates or query name

• bamtofastq: reads BAM and writes FastQ; output can be collated or uncollated by query name.

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.

The package reads phylogenetic data in the phyloXML format. It also includes functions for writing data in this format.

This is a collection of utility functions for Seurat. These functions allow the automation and multiplexing of plotting, 3D plotting, visualization of statistics & QC, interaction with the Seurat object. Some functionalities require functions from CodeAndRoll and MarkdownReports libraries.

Scanorama enables batch-correction and integration of heterogeneous scRNA-seq datasets, which is described in the paper "Efficient integration of heterogeneous single-cell transcriptomes using Scanorama" by Brian Hie, Bryan Bryson, and Bonnie Berger.

This package is used for demultiplexing single-cell sequencing experiments of pooled cells. These cells are labeled with barcode oligonucleotides. The package implements methods to fit regression mixture models for a probabilistic classification of cells, including multiplet detection. Demultiplexing error rates can be estimated, and methods for quality control are provided.

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

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