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http://bioinformatics.ubc.ca/ermineJ/

Data analysis software for gene sets in expression microarray data or other genome-wide data that results in rankings of genes. A typical goal is to determine whether particular biological pathways are doing something interesting in the data. The software is designed to be used by biologists with little or no informatics background. A command-line interface is available for users who wish to script the use of ermineJ. Major features include: * Implementation of multiple methods for gene set analysis: ** Over-representation analysis ** A resampling-based method that uses gene scores ** A rank-based method that uses gene scores ** A resampling-based method that uses correlation between gene expression profiles (a type of cluster-enrichment analysis). * Gene sets receive statistical scores (p-values), and multiple test correction is supported. * Support of the Gene Ontology terminology; users can choose which aspects to analyze. * User files use simple text formats. * Users can modify gene sets or create new ones. * The results can be visualized within the software. * It is simple to compare multiple analyses of the same data set with different settings. * User-definable hyperlinks are provided to external sites to allow more efficient browsing of the results. * For programmers, there is a command line interface as well as a simple application programming interface that can be used to plug ermineJ functionality into your own code Platform: Online tool, Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: ErmineJ (RRID:SCR_006450) Copy   

•   Source: SciCrunch Registry

http://www.ebi.ac.uk/ena/

Public archive providing a comprehensive record of the world''''s nucleotide sequencing information, covering raw sequencing data, sequence assembly information and functional annotation. All submitted data, once public, will be exchanged with the NCBI and DDBJ as part of the INSDC data exchange agreement. The European Nucleotide Archive (ENA) captures and presents information relating to experimental workflows that are based around nucleotide sequencing. A typical workflow includes the isolation and preparation of material for sequencing, a run of a sequencing machine in which sequencing data are produced and a subsequent bioinformatic analysis pipeline. ENA records this information in a data model that covers input information (sample, experimental setup, machine configuration), output machine data (sequence traces, reads and quality scores) and interpreted information (assembly, mapping, functional annotation). Data arrive at ENA from a variety of sources including submissions of raw data, assembled sequences and annotation from small-scale sequencing efforts, data provision from the major European sequencing centers and routine and comprehensive exchange with their partners in the International Nucleotide Sequence Database Collaboration (INSDC). Provision of nucleotide sequence data to ENA or its INSDC partners has become a central and mandatory step in the dissemination of research findings to the scientific community. ENA works with publishers of scientific literature and funding bodies to ensure compliance with these principles and to provide optimal submission systems and data access tools that work seamlessly with the published literature. ENA is made up of a number of distinct databases that includes the EMBL Nucleotide Sequence Database (Embl-Bank), the newly established Sequence Read Archive (SRA) and the Trace Archive. The main tool for downloading ENA data is the ENA Browser, which is available through REST URLs for easy programmatic use. All ENA data are available through the ENA Browser. Note: EMBL Nucleotide Sequence Database (EMBL-Bank) is entirely included within this resource.

Proper citation: European Nucleotide Archive (ENA) (RRID:SCR_006515) Copy   

•   Source: SciCrunch Registry

https://github.com/markmikkelsen/Gannet

Free, open-source MATLAB-based software toolkit for analyzing edited 1H magnetic resonance spectroscopy (MRS) data.

Proper citation: Gannet (RRID:SCR_016049) Copy   

•   Source: SciCrunch Registry

https://gitlab.com/SimonHTausch/HiLive

Software tool for performing read mapping that maps Illumina HiSeq sequencer read alignments when they are produced. Used in Next Generation Sequencing in time critical, clinical applications.

Proper citation: HiLive (RRID:SCR_016134) Copy   

•   Source: SciCrunch Registry

https://www.jamovi.org/

Software for statistical analysis and spreadsheet editing that is built on top of the R statistical language. It encourages a “community driven” philosophy, where users can develop and publish their analyses to make them available to a wide audience.

Proper citation: jamovi (RRID:SCR_016142) Copy   

•   Source: SciCrunch Registry

https://github.com/Ashod/garli

Software application for inferring phylogenetic trees and analysis of molecular sequence data using the maximum-likelihood criterion. It implements nucleotide, amino acid and codon-based models of sequence evolution.

Proper citation: GARLI (RRID:SCR_016117) Copy   

•   Source: SciCrunch Registry

https://github.com/nvalimak/fsm-lite

Software application as a single-core implementation of frequency-based substring mining. It can be used in bioinformatics to extract substrings that discriminate two (or more) datasets inside high-throughput sequencing data.

Proper citation: Fsm-lite (RRID:SCR_016115) Copy   

•   Source: SciCrunch Registry

https://github.com/bbuchfink/diamond

Software that performs sequence alignment for protein and translated DNA searches and functions. Used for high performance analysis of big sequence data, protein-protein search, and DNA-protein search.

Proper citation: DIAMOND (RRID:SCR_016071) Copy   

•   Source: SciCrunch Registry

http://acb.qfab.org/acb/glam2/

Software package for finding novel, gapped (recurring, variable-length patterns) motifs in related groups of DNA or protein sequences (sample output from sequences). Used to perform motif based sequence discovery for gapped motifs on DNA or protein datasets.

Proper citation: Glam2 (RRID:SCR_016129) Copy   

•   Source: SciCrunch Registry

http://genometools.org

Software toolkit for biological sequence analysis and -presentation combined into a single binary. It is used for genome analysis, efficient processing of structured genome annotations and contains binaries for sequence and annotation handling, sequence compression, index structure generation and access, annotation visualization.

Proper citation: GenomeTools (RRID:SCR_016120) Copy   

•   Source: SciCrunch Registry

https://cell-innovation.nig.ac.jp/maser/Tools/visualization_top_en.html

One stop platform for NGS big data from analysis to visualization. There are about 400 analysis pipelines integrated on Maser. List of all analysis pipelines, including descriptions and approximate execution times, can be found on page for ‘All pipelines’ in the User Guide. loadGtfToGe_db software loads GTF files to a database for Genome Explorer. It allows the user to browse the results through the GE.

Proper citation: loadGtfToGe_db (RRID:SCR_015998) Copy   

•   Source: SciCrunch Registry

https://savannah.gnu.org/projects/datamash/

Software for a command-line interface which performs basic numeric, textual and statistical operations on input textual data files. It is designed to aid researchers in automating analysis pipelines, without writing code or short scripts.

Proper citation: Datamash (RRID:SCR_016067) Copy   

•   Source: SciCrunch Registry

https://gemma.msl.ubc.ca/phenotypes.html

Database that consolidates information on genes and phenotypes across multiple resources and allows tracking and exploring of the associations. Part of Gemma, a web site, database and a set of tools for the meta-analysis, re-use and sharing of genomics data.

Proper citation: Phenocarta (RRID:SCR_016273) Copy   

•   Source: SciCrunch Registry

http://aspiredb.msl.ubc.ca/

Web based software for analyzing genomic variants CNVs, SNVs, and Indels and phenotypes. It aims to represent the relationships between discovered variants and phenotypes.

Proper citation: AspireDB (RRID:SCR_016272) Copy   

•   Source: SciCrunch Registry

https://www.picoquant.com/products/category/software

Software for fluorescence lifetime imaging and correlation. SymPhoTime 64 is the data acquisition software for PicoQuant's time-resolved confocal microscope MicroTime 200 and LSM upgrade kits.

Proper citation: SymPhoTime 64 (RRID:SCR_016263) Copy   

•   Source: SciCrunch Registry

http://www.birds.cornell.edu/brp/raven/RavenOverview.html

Software for the acquisition, visualization, measurement, and analysis of sounds. Raven supports annotations for research-related analysis.

Proper citation: Raven (RRID:SCR_016190) Copy   

•   Source: SciCrunch Registry

http://www.heka.com/downloads/downloads_main.html#down_fitmaster

Software for analysis and fitting routines of electrophysiological data. Analysis can be performed on the levels of Sweeps/Traces and Series.

Proper citation: FITMASTER (RRID:SCR_016233) Copy   

•   Source: SciCrunch Registry

http://www.redshirtimaging.com/redshirt_neuro/software_aquisition.htm

Software for acquisition and analysis for imaging applications. The acquisition section has a variety of triggering and averaging modes, while the analysis section has extensive provisions for displaying traces (intensity vs time) and movies of propagating activity.

Proper citation: NeuroPlex (RRID:SCR_016193) Copy   

•   Source: SciCrunch Registry

https://fractalis.lcsb.uni.lu/

Software as a scalable open-source service for platform-independent interactive visual analysis of biomedical data. It is a service and a library that work in tandem to equip existing platforms with visual analytical capabilities for explorative data analysis.

Proper citation: Fractalis (RRID:SCR_016362) Copy   

•   Source: SciCrunch Registry

http://cole-trapnell-lab.github.io/monocle-release/docs/

Software package for analyzing single cell gene expression, classifying and counting cells, performing differential expression analysis between subpopulations of cells, and reconstructing cellular trajcectories. Works well with very large single-cell RNA-Seq experiments containing tens of thousands of cells or more. Used in computational analysis of gene expression data in single cell gene expression studies to profile transcriptional regulation in complex biological processes and highly heterogeneous cell populations.

Proper citation: Monocle2 (RRID:SCR_016339) Copy   

•   Source: SciCrunch Registry