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.

NanoSV is a software package that can be used to identify structural genomic variations in long-read sequencing data, such as data produced by Oxford Nanopore Technologies’ MinION, GridION or PromethION instruments, or Pacific Biosciences RSII or Sequel sequencers.

This framework facilitates the execution of differential junction usage (DJU) methods. Additionally, it enables the integration of results from multiple DJU methods.

The alignment module of BioJava provides an API that contains

• implementations of dynamic programming algorithms for sequence alignment;

• reading and writing of popular alignment file formats;

• a single-, or multi- threaded multiple sequence alignment algorithm.

CrossMap is a program for conversion of genome coordinates or annotation files between different genome assemblies. It supports most commonly used file formats including SAM/BAM, Wiggle/BigWig, BED, GFF/GTF, VCF.

QTLtools is a tool set for molecular QTL discovery and analysis. It allows going from the raw genetic sequence data to collection of molecular Quantitative Trait Loci (QTLs) in few easy-to-perform steps.

BWA-Meth works for single-end reads and for paired-end reads from the directional protocol (most common). It uses the method employed by methylcoder and Bismark of in silico conversion of all C's to T's in both reference and reads. It recovers the original read (needed to tabulate methylation) by attaching it as a comment which BWA appends as a tag to the read. It performs favorably to existing aligners gauged by number of on and off-target reads for a capture method that targets CpG-rich region.

Model-based Analysis of Genome-wide CRISPR-Cas9 Knockout (MAGeCK) is a computational tool to identify important genes from the recent genome-scale CRISPR-Cas9 knockout screens technology. Its features include:

1. Simple, easy to use pipeline to screen genes in Genome-wide CRISPR-Cas9 Knockout experiments;

2. High sensitivity and low false discovery rate;

3. Fully utilize the screening data by performing both positive and negative screening in one dataset;

4. Provide statistical evaluation in genes, sgRNAs and pathways;

5. Require as few as 2 samples;

6. Identify cell-type specific targets;

7. A set of visualization features that generate publication standard figures.

This package provides Python bindings for spoa, a C++ implementation of the partial order alignment (POA) algorithm (as described in 10.1093/bioinformatics/18.3.452) which is used to generate consensus sequences

This is a package for fast Non-negative Matrix Factorization (NMF) with automatic rank-determination for dimension reduction of single-cell data using Seurat, RcppML nmf, SingleCellExperiments and similar.

Salmon is a program to produce highly-accurate, transcript-level quantification estimates from RNA-seq data. Salmon achieves its accuracy and speed via a number of different innovations, including the use of lightweight alignments (accurate but fast-to-compute proxies for traditional read alignments) and massively-parallel stochastic collapsed variational inference.

eXpress is a streaming tool for quantifying the abundances of a set of target sequences from sampled subsequences. Example applications include transcript-level RNA-Seq quantification, allele-specific/haplotype expression analysis (from RNA-Seq), transcription factor binding quantification in ChIP-Seq, and analysis of metagenomic data.

This package provides R miscellaneous utilities for basic data manipulation, debugging, visualization, lsf management, and common mskilab tasks.

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.

Pairtools is a simple and fast command-line framework to process sequencing data from a Hi-C experiment. Process pair-end sequence alignments and perform the following operations:

• detect ligation junctions (a.k.a. Hi-C pairs) in aligned paired-end sequences of Hi-C DNA molecules

• sort .pairs files for downstream analyses

• detect, tag and remove PCR/optical duplicates

• generate extensive statistics of Hi-C datasets

• select Hi-C pairs given flexibly defined criteria

• restore .sam alignments from Hi-C pairs.

Express Beta Diversity (EBD) calculates ecological beta diversity (dissimilarity) measures between biological communities. EBD implements a variety of diversity measures including those that make use of phylogenetic similarity of community members.

Pysam is a Python module for reading and manipulating files in the SAM/BAM format. Pysam is a lightweight wrapper of the SAMtools C API. It also includes an interface for tabix.

CNVkit is a Python library and command-line software toolkit to infer and visualize copy number from high-throughput DNA sequencing data. It is designed for use with hybrid capture, including both whole-exome and custom target panels, and short-read sequencing platforms such as Illumina and Ion Torrent.

This library contains the genomics components of the Bio++ sequence library. It is part of the Bio++ project.

Jellyfish is a tool for fast, memory-efficient counting of k-mers in DNA. A k-mer is a substring of length k, and counting the occurrences of all such substrings is a central step in many analyses of DNA sequence. Jellyfish is a command-line program that reads FASTA and multi-FASTA files containing DNA sequences. It outputs its k-mer counts in a binary format, which can be translated into a human-readable text format using the jellyfish dump command, or queried for specific k-mers with jellyfish query.

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.

This package provides necessary tools for the analysis of the genomic interaction data stored in .cool format. This collection of tools includes operations like compartment, insulation or peak calling.

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.

This package is used for cell type identification in spatial transcriptomics. It also handles cell type-specific differential expression.