BioGrids is available to all Harvard affiliates on a trial basis for the 2019 calendar year.
Register here to try out our software installer, which allows users to choose from over 200 bioinfomatics tools that can be installed as ready-to-run applications on Mac or Linux machines with the click of a button or a short command from the CLI. No need to worry about dependencies or compilation.
BioGrids is supported by a team of scientists and engineers at HMS. We provide direct support to BioGrids members. This includes all aspects of software installation and management. If you need assistance of any kind please send a note to: email@example.com.
The BioGrids Installer is an easy to use application that makes installing and managing life sciences software simple and quick.
A command line version is also available for Macs and Linux. Download using the link button above and register here for activation.
The BioGrids team provides support, infrastructure and testing for scientific software packages. We currently provide over 200 titles in five categories and an additional 1,500 R, python and perl packages and modules. The collection grows weekly. Learn more here: About BioGrids
If you are new to BioGrids and would like to quickly get started with the command line version, follow the instructions below:
1: Download the BioGrids Installer command line version
./biogrids activate biogrid-production jvinent1 70rYFTDnmCr93VUklfbf1s3M4jdyC9bFVYHew==
Replace the site name, user name and activation key with your own credentials.
3: Install software with BioGrids
./biogrids install fastqc trimmomatic samtools star subread igv
When finished, verify applications are installed:
MAFFT is a multiple sequence alignment program for unix-like operating systems. It offers a range of multiple alignment methods, L-INS-i (accurate; for alignment of <200 sequences), FFT-NS-2 (fast; for alignment of <30,000 sequences).
IGV is a high-performance visualization tool for interactive exploration of large, integrated genomic datasets. It supports a wide variety of data types, including array-based and next-generation sequence data, and genomic annotations.
OpenMS is an open-source software C++ library for LC-MS data management and analyses. It offers an infrastructure for rapid development of mass spectrometry related software.
juicer is a one-click pipeline for processing terabase scale Hi-C datasets. Using Juicer, you can:
Go from raw fastq files to Hi-C maps binned at many resolutions Automatically annotate loops and contact domains with the Juicer tools Run the pipeline in the cloud, on LSF, Univa, or SLURM, or on a single CPU
Juicer creates hic files from raw (unaligned) reads derived from a Hi-C experiment.
Phantompeakqualtools computes informative enrichment and quality measures for ChIP-seq/DNase-seq/FAIRE-seq/MNase-seq data. It can also be used to obtain robust estimates of the predominant fragment length or characteristic tag shift values in these assays.
FFmpeg is a complete, cross-platform solution to record, convert and stream audio and video.
deepTools addresses the challenge of handling the large amounts of data that are now routinely generated from DNA sequencing centers. deepTools contains useful modules to process the mapped reads data for multiple quality checks, creating normalized coverage files in standard bedGraph and bigWig file formats, that allow comparison between different files (for example, treatment and control). Finally, using such normalized and standardized files, deepTools can create many publication-ready visualizations to identify enrichments and for functional annotations of the genome.
HTSeq is a Python package that provides infrastructure to process data from high-throughput sequencing assays.
MACS2 (Model Based Analysis of ChIP-Seq data) is a novel algorithm for identifying transcript factor binding sites.
FASTA is a DNA and protein sequence alignment software package that searches for matching sequence patterns or words, called k-tuples.
PyMC3 is a Python package for Bayesian statistical modeling and Probabilistic Machine Learning focusing on advanced Markov chain Monte Carlo (MCMC) and variational inference (VI) algorithms. Its flexibility and extensibility make it applicable to a large suite of problems.