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http://www.gaworkshop.org/

The Genetic Analysis Workshops (GAWs) are a collaborative effort among genetic epidemiologists to evaluate and compare statistical genetic methods. For each GAW, topics are chosen that are relevant to current analytical problems in genetic epidemiology, and sets of real or computer-simulated data are distributed to investigators worldwide. Results of analyses are discussed and compared at meetings held in even-numbered years. The GAWs began in 1982 were initially motivated by the development and publication of several new algorithms for statistical genetic analysis, as well as by reports in the literature in which different investigators, using different methods of analysis, had reached contradictory conclusions. The impetus was initially to determine the numerical accuracy of the algorithms, to examine the robustness of the methodologies to violations of assumptions, and finally, to compare the range of conclusions that could be drawn from a single set of data. The Workshops have evolved to include consideration of problems related to analyses of specific complex traits, but the focus has always been on analytical methods. The Workshops provide an opportunity for participants to interact in addressing methodological issues, to test novel methods on the same well-characterized data sets, to compare results and interpretations, and to discuss current problems in genetic analysis. The Workshop discussions are a forum for investigators who are evolving new methods of analysis as well as for those who wish to gain further experience with existing methods. The success of the Workshops is due at least in part to the focus on specific problems and data sets, the informality of sessions, and the requirement that everyone who attends must have made a contribution. Topics are chosen and a small group of organizers is selected by the GAW Advisory Committee. Data sets are assembled, and six or seven months before each GAW, a memo is sent to individuals on the GAW mailing list announcing the availability of the GAW data. Included with the memo is a short description of the data sets and a form for requesting data. The form contains a statement to be signed by any investigator requesting the data, acknowledging that the data are confidential and agreeing not to use them for any purpose other than the Genetic Analysis Workshop without written permission from the data provider(s). Data are distributed by the ftp or CD-ROM or, most recently, on the web, together with a more complete written description of the data sets. Investigators who wish to participate in GAW submit written contributions approximately 6-8 weeks before the Workshop. The GAW Advisory Committee reviews contributions for relevance to the GAW topics. Contributions are assembled and distributed to all participants approximately two weeks before the Workshop. Participation in the GAWs is limited to investigators who (1) submit results of their analyses for presentation at the Workshop, or (2) are data providers, invited speakers or discussants, or Workshop organizers. GAWs are held just before the meetings of the American Society of Human Genetics or the International Genetic Epidemiology Society, at a meeting site nearby. We choose a location that will encourage interaction among participants and permit an intense period of concentrated work. The proceedings of each GAW are published. Proceedings from GAW16 were published in part by Genetic Epidemiology 33(Suppl 1), S1-S110 (2009) and in part by Biomed Central (BMC Proceedings, Volume 3, Supplement 7, 2009). Sponsors: GAW is funded by the Southwest Foundation for Biomedical Research.

Proper citation: Genetic Analysis Workshop (RRID:SCR_008350) Copy   

•   Source: SciCrunch Registry

https://biocodecommons.org/

Platform provides resources for genomic observations from collection to analysis and publication. Works with standards community to ensure clear vocabularies and useful ontologies for biological resources and related assets. Biocode Commons is also collaborating on development of Biological Collections Ontology, working to better integrate ontologies, vocabularies, and relevant standards that are related to BCO.

Proper citation: Biocode Commons (RRID:SCR_024553) Copy   

•   Source: SciCrunch Registry

http://rfmri.org/DPARSF

A MATLAB toolbox forpipeline data analysis of resting-state fMRI that is based on Statistical Parametric Mapping (SPM) and a plug-in software within DPABI. After the user arranges the Digital Imaging and Communications in Medicine (DICOM) files and click a few buttons to set parameters, DPARSF will then give all the preprocessed (slice timing, realign, normalize, smooth) data and results for functional connectivity, regional homogeneity, amplitude of low-frequency fluctuation (ALFF), fractional ALFF, degree centrality, voxel-mirrored homotopic connectivity (VMHC) results. DPARSF can also create a report for excluding subjects with excessive head motion and generate a set of pictures for easily checking the effect of normalization. In addition, users can also use DPARSF to extract time courses from regions of interest. DPARSF basic edition is very easy to use while DPARSF advanced edition (alias: DPARSFA) is much more flexible and powerful. DPARSFA can parallel the computation for each subject, and can be used to reorient images interactively or define regions of interest interactively. Users can skip or combine the processing steps in DPARSF advanced edition freely.

Proper citation: DPARSF (RRID:SCR_002372) Copy   

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http://icatb.sourceforge.net/fusion/fusion_startup.php

A MATLAB toolbox which implements the joint Independent Component Analysis (ICA), parallel ICA and CCA with joint ICA methods. It is used to to extract the shared information across modalities like fMRI, EEG, sMRI and SNP data. * Environment: Win32 (MS Windows), Gnome, KDE * Operating System: MacOS, Windows, Linux * Programming Language: MATLAB * Supported Data Format: ANALYZE, NIfTI-1

Proper citation: Fusion ICA Toolbox (RRID:SCR_003494) Copy   

•   Source: SciCrunch Registry

http://gephi.org/

Open-source software for network visualization and analysis helping data analysts to intuitively reveal patterns and trends, highlight outliers and tells stories with their data. It uses a 3D render engine to display large graphs in real-time and to speed up the exploration. Gephi combines built-in functionalities and flexible architecture to: explore, analyze, spatialize, filter, cluterize, manipulate and export all types of networks. Gephi runs on Windows, Linux and Mac OS X. Gephi is based on a visualize-and-manipulate paradigm which allow any user to discover networks and data properties. Moreover, it is designed to follow the chain of a case study, from data file to nice printable maps. It is open-source and free (GNU General Public License). Applications: * Exploratory Data Analysis: intuition-oriented analysis by networks manipulations in real time. * Link Analysis: revealing the underlying structures of associations between objects, in particular in scale-free networks. * Social Network Analysis: easy creation of social data connectors to map community organizations and small-world networks. * Biological Network analysis: representing patterns of biological data. * Poster creation: scientific work promotion with hi-quality printable maps. Gephi 0.7 architecture is modular and therefore allows developers to add and extend functionalities with ease. New features like Metrics, Layout, Filters, Data sources and more can be easily packaged in plugins and shared. The built-in Plugins Center automatically gets the list of plugins available from the Gephi Plugin portal and takes care of all software updates. Download, comment, and rate plugins provided by community members and third-party companies, or post your own contributions!

Proper citation: Gephi (RRID:SCR_004293) Copy   

•   Source: SciCrunch Registry

http://bioinformatics.biol.rug.nl/standalone/fiva/

Functional Information Viewer and Analyzer (FIVA) aids researchers in the prokaryotic community to quickly identify relevant biological processes following transcriptome analysis. Our software is able to assist in functional profiling of large sets of genes and generates a comprehensive overview of affected biological processes. Currently, seven different modules containing functional information have been implemented: (i) gene regulatory interactions, (ii) cluster of orthologous groups (COG) of proteins, (iii) gene ontologies (GO), (iv) metabolic pathways (v) Swiss Prot keywords, (vi) InterPro domains - and (vii) generic functional categories. Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: FIVA - Functional Information Viewer and Analyzer (RRID:SCR_005776) Copy   

•   Source: SciCrunch Registry

http://ftp://ftp.geneontology.org/pub/go/www/GO.tools_by_type.term_enrichment.shtml#gobean

GoBean is a Java application for gene ontology enrichment analysis. It utilizes the NetBeans platform framework. Features * Graphical comparison of multiple enrichment analysis results * Versatile filter facility for focused analysis of enrichment results * Effective exploitation of the graphical/hierarchical structure of GO * Evidence code based association filtering * Supports local data files such as the ontology obo file and gene association files * Supports late enrichment methods and multiple testing corrections * Built-in ID conversion for common species using Ensembl biomart service Platform: Windows compatible, Mac OS X compatible, Linux compatible

Proper citation: GoBean - a Java application for Gene Ontology enrichment analysis (RRID:SCR_005808) Copy   

•   Source: SciCrunch Registry

http://www.seqexpress.com/

A comprehensive analysis and visualization software package for gene expression experiments that provides: a number of clustering and analysis techniques; integrated gene expression and analysis result visualizations, integration with the Gene Expression Omnibus; and an optional data sharing architecture. GO is used to assign functional enrichment scores to clusters, using a combination of specially developed techniques and general statistical methods. These results can be explored using the in built ontology browsing tool or through the generated web pages. SeqExpress also supports numerous data transformation, projection, visualization, file export/import, searching, integration (with R), and clustering options.

Proper citation: SeqExpress (RRID:SCR_007075) Copy   

•   Source: SciCrunch Registry

http://rfmri.org/dpabi

Software toolbox for data processing and analysis of brain imaging, evolved from DPARSF (Data Processing Assistant for Resting-State fMRI).

Proper citation: DPABI (RRID:SCR_010501) Copy   

•   Source: SciCrunch Registry

https://github.com/facebook/prophet

Open source software package for producing forecasts for time series data that has multiple seasonality with linear or non linear growth. Implemented in R or Phyton.

Proper citation: Prophet (RRID:SCR_017083) Copy   

•   Source: SciCrunch Registry

http://hmri.info

Software toolbox for quantitative MRI in neuroscience and clinical research. Open source and flexible tool for qMRI data handling and processing. Allows estimation of high quality multi parameter qMRI maps followed by spatial registration in common space for statistical analysis.

Proper citation: hMRI-toolbox (RRID:SCR_017682) Copy   

•   Source: SciCrunch Registry

https://gitlab.com/PlantGenomicsLab/gFACs

Software package provides comprehensive framework for evaluating, filtering, and analyzing gene models from range of input applications and preparing these annotations for formal publication or downstream analysis.

Proper citation: gFACs (RRID:SCR_022017) Copy   

•   Source: SciCrunch Registry

http://www.nanostring.com/products/nSolver

Data analysis software program that offers nCounter users the ability to QC, normalize, and analyze data without having to purchase additional software packages.

Proper citation: nSolver Analysis Software (RRID:SCR_003420) Copy   

•   Source: SciCrunch Registry

http://www.scienceexchange.com/facilities/macquarie-university

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 23,2023. Set of facilities based out of Macquarie University in New South Wales. Some facilities provide services such as proteome analysis or resources of various academic departments like engineering, biological sciences, and geography.

Proper citation: Macquarie University Labs and Facilities (RRID:SCR_000944) Copy   

•   Source: SciCrunch Registry

http://nrnb.org/index.html

Biomedical technology research center that develops new algorithms, visualizations and conceptual frameworks to study biological networks at multiple levels and scales, from protein-protein and genetic interactions to cell-cell communication and vast social networks. They are developing freely available, open-source suite of software technology that broadly enables network-based visualization, analysis, and biomedical discovery for NIH-funded researchers. This software is enabling researchers to assemble large-scale biological data into models of networks and pathways and to use these networks to better understand how biological systems operate under normal conditions and how they fail in disease. The National Resource for Network Biology is organized around the following key components: Technology Research and Development, Driving Biomedical Projects, Outreach, Training and Dissemination of Tools. The NRNB supports several types of training events, including both virtual and live workshops; tutorials sessions for clinicians, biologists and bioinformaticians; presentations and demonstrations at conferences; online tutorials and webcasts; and annual symposium.

Proper citation: National Resource for Network Biology (RRID:SCR_004259) Copy   

•   Source: SciCrunch Registry

http://msr.dom.wustl.edu/

Biomedical technology research center that develops mass spectrometry-based tools for the study of proteins, lipids and metaboilites. These include biomarker identification, stable isotope mass spectrometry and the analysis of intact proteins. Our goals are: * to conduct basic research in the science of mass spectrometry * to establish collaborative research projects with scientists at WU and at other institutions * to provide a service in mass spectrometry * to educate and train students in mass spectrometry * to disseminate results of our research and descriptions of the subject of mass spectrometry

Proper citation: NIH / NCRR Mass Spectrometry Resource Washington University in St. Louis (RRID:SCR_009009) Copy   

•   Source: SciCrunch Registry

http://www.genmapp.org/

GenMAPP is a free computer application designed to visualize gene expression and other genomic data on maps representing biological pathways and groupings of genes. Integrated with GenMAPP are programs to perform a global analysis of gene expression or genomic data in the context of hundreds of pathway MAPPs and thousands of Gene Ontology Terms (MAPPFinder), import lists of genes/proteins to build new MAPPs (MAPPBuilder), and export archives of MAPPs and expression/genomic data to the web. The main features underlying GenMAPP are: *Draw pathways with easy to use graphics tools *Color genes on MAPP files based on user-imported genomic data *Query data against MAPPs and the GeneOntology Enhanced features include the simultaneous view of multiple color sets, expanded species-specific gene databases and custom database options.

Proper citation: Gene Map Annotator and Pathway Profiler (RRID:SCR_005094) Copy   

•   Source: SciCrunch Registry

http://primegens.org/

A Web-based Tool for High-throughput Primer and Probe Design. The program has its different utilities available on its web server. A standalone version is also available. Algorithms: * SSPD - Sequence Specific Primer Design: to design primers for each of the specific sequences given by the user in the query input file against any alternate potential hybridization with any of the sequences given in the database input file. * PSPD - Probe Specific Primer Design: to design primers it selects the gene-specific fragments (probes) to design primer pairs for their PCR amplification. * FSPD Fragment Specific Primer Design: primer design algorithm used when there is a very long query sequence for which multiple primers are required for its amplification. * Check Binding Specificity * Probe Design Only: Probe design algorithm could be used to find sequence-specific probes, which doesn''t show any blast hit against database. Such probe design has been used for targeted sequencing like agilent sure-select technology with next-generation sequencing.

Proper citation: PRIMEGENS (RRID:SCR_005474) Copy   

•   Source: SciCrunch Registry

http://bowtie-bio.sourceforge.net/index.shtml

Software ultrafast memory efficient tool for aligning sequencing reads. Bowtie is short read aligner.

Proper citation: Bowtie (RRID:SCR_005476) Copy   

•   Source: SciCrunch Registry

http://www.cma.mgh.harvard.edu/iatr/

A centrally available listing of all image analysis tools that are available to the neuroscience community in order to facilitate the development, identification, and sharing of tools. It is hoped that this helps the tool developers to get their tools to a larger user community and to reduce redundancy (or at least utilize tool redundancy to facilitate optimal tool design) in tool development. This also helps tool users in identification of the existing tools for specific problems as they arise. The registry is designed to be self-moderated. This means that all tool entries are owned by some responsible party who enters the tool information, and keeps it up to date via the Web.

Proper citation: Internet Analysis Tools Registry (RRID:SCR_005638) Copy   

•   Source: SciCrunch Registry