This package provides a package that makes it easy to implement sankey, alluvial and sankey bump plots in ggplot2.

SeuratWrappers is a collection of community-provided methods and extensions for Seurat, curated by the Satija Lab at NYGC. These methods comprise functionality not presently found in Seurat, and are able to be updated much more frequently.

BEDOPS is a suite of tools to address common questions raised in genomic studies---mostly with regard to overlap and proximity relationships between data sets. It aims to be scalable and flexible, facilitating the efficient and accurate analysis and management of large-scale genomic data.

BEDOPS provides tools that perform highly efficient and scalable Boolean and other set operations, statistical calculations, archiving, conversion and other management of genomic data of arbitrary scale. Tasks can be easily split by chromosome for distributing whole-genome analyses across a computational cluster.

Chromap is a fast method for aligning and preprocessing high throughput chromatin profiles. Typical use cases include:

• trimming sequencing adapters, mapping bulk ATAC-seq or ChIP-seq genomic reads to the human genome and removing duplicates;

• trimming sequencing adapters, mapping single cell ATAC-seq genomic reads to the human genome, correcting barcodes, removing duplicates and performing Tn5 shift;

• split alignment of Hi-C reads against a reference genome.

PiGX scRNAseq is an analysis pipeline for preprocessing and quality control for single cell RNA sequencing experiments. The inputs are read files from the sequencing experiment, and a configuration file which describes the experiment. It produces processed files for downstream analysis and interactive quality reports. The pipeline is designed to work with UMI based methods.

This package provides the ASCAT R package that can be used to infer tumour purity, ploidy and allele-specific copy number profiles.

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.

PiGx SARS-CoV-2 is a pipeline for analysing data from sequenced wastewater samples and identifying given variants-of-concern of SARS-CoV-2. The pipeline can be used for continuous sampling. The output report will provide an intuitive visual overview about the development of variant abundance over time and location.

SQUID is Sean Eddy's personal library of C functions and utility programs for sequence analysis.

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.

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).

This is an R package that integrates the installation of doublet-detection methods. In addition, this tool is used for execution and benchmark of those eight mentioned methods.

BSeq-sc is a bioinformatics analysis pipeline that leverages single-cell sequencing data to estimate cell type proportion and cell type-specific gene expression differences from RNA-seq data from bulk tissue samples. This is a companion package to the publication "A single-cell transcriptomic map of the human and mouse pancreas reveals inter- and intra-cell population structure." Baron et al. Cell Systems (2016) https://www.ncbi.nlm.nih.gov/pubmed/27667365.

RAxML is a tool for phylogenetic analysis and post-analysis of large phylogenies.

This package provides TagGD barcode demultiplexing utilities for Spatial Transcriptomics data.

F-Seq is a software package that generates a continuous tag sequence density estimation allowing identification of biologically meaningful sites such as transcription factor binding sites (ChIP-seq) or regions of open chromatin (DNase-seq). Output can be displayed directly in the UCSC Genome Browser.

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.

PRINSEQ is a bioinformatics tool to help you preprocess your genomic or metagenomic sequence data in FASTA or FASTQ formats. The tool is written in Perl and can be helpful if you want to filter, reformat, or trim your sequence data. It also generates basic statistics for your sequences.

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.

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.

Bio-locus is a tabix-like tool for fast querying of genome locations. Many file formats in bioinformatics contain records that start with a chromosome name and a position for a SNP, or a start-end position for indels. Bio-locus allows users to store this chr+pos or chr+pos+alt information in a database.

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.

IMP's broad goal is to contribute to a comprehensive structural characterization of biomolecules ranging in size and complexity from small peptides to large macromolecular assemblies, by integrating data from diverse biochemical and biophysical experiments. IMP provides a C++ and Python toolbox for solving complex modeling problems, and a number of applications for tackling some common problems in a user-friendly way.

PAIRADISE is a method for detecting allele-specific alternative splicing (ASAS) from RNA-seq data. Unlike conventional approaches that detect ASAS events one sample at a time, PAIRADISE aggregates ASAS signals across multiple individuals in a population. By treating the two alleles of an individual as paired, and multiple individuals sharing a heterozygous SNP as replicates, PAIRADISE formulates ASAS detection as a statistical problem for identifying differential alternative splicing from RNA-seq data with paired replicates.