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http://compbio.bccrc.ca/software/mutationseq/

A software suite using feature-based classifiers for somatic mutation prediction from paired tumour/normal next-generation sequencing data. mutationSeq has the advantages of integrating different features (e.g., base qualities, mapping qualities, strand bias, and tailed distance features), and validated somatic mutations to make predictions. Given paired normal/tumour bam files, mutationSeq will output the probability of each candidate site being somatic.

Proper citation: mutationSeq (RRID:SCR_006815) Copy   

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http://www.broadinstitute.org/cancer/cga/absolute

Software to estimate purity / ploidy, and from that compute absolute copy-number and mutation multiplicities. When DNA is extracted from an admixed population of cancer and normal cells, the information on absolute copy number per cancer cell is lost in the mixing. The purpose of ABSOLUTE is to re-extract these data from the mixed DNA population. This process begins by generation of segmented copy number data, which is input to the ABSOLUTE algorithm together with pre-computed models of recurrent cancer karyotypes and, optionally, allelic fraction values for somatic point mutations. The output of ABSOLUTE then provides re-extracted information on the absolute cellular copy number of local DNA segments and, for point mutations, the number of mutated alleles.

Proper citation: ABSOLUTE (RRID:SCR_005198) Copy   

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http://www.iro.umontreal.ca/~csuros/quadgt/

Software package for calling single-nucleotide variants in four sequenced genomes comprising a normal-tumor pair and the two parents. Genotypes are inferred using a joint model of parental variant frequencies, de novo germline mutations, and somatic mutations. The model quantifies the descent-by-modification relationships between the unknown genotypes by using a set of parameters in a Bayesian inference setting. Note that you can use it on any subset of the four related genomes, including parent-offspring trios, and normal-tumor pairs without parental samples.

Proper citation: QuadGT (RRID:SCR_000073) Copy   

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http://www.psoriasis.org/netcommunity/act_biobank

The National Psoriasis Victor Henschel BioBank is a collection of biological samples and clinical information used by qualified scientists to further the field of psoriasis genetics. Once completed, the National Psoriasis BioBank will be the largest collection of psoriasis DNA samples in the world, moving us closer to understanding the causes of psoriatic diseases, discovering more and better treatments and finding a cure. The BioBank is currently collecting DNA from people with and without psoriasis and/or psoriatic arthritis. Simply by donating your DNA����??a blood sample and a swab of your cheek cells����??and providing us with your medical history, you can help us find a cure. Samples will be processed and stored at a private laboratory and not at the National Psoriasis Foundation. The National Psoriasis BioBank is part of the Genetic Alliance BioBank (GA BioBank), a centralized repository for the collection, storage and distribution of biological samples (including DNA, serum, cells and tissues) and clinical data for genetic researchers.

Proper citation: National Psoriasis BioBank (RRID:SCR_010537) Copy   

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http://www.tcd.ie/IMM/trinity-biobank/index.php

The Trinity Biobank was established in 2005 to serve the needs of researchers in the area of genetic epidemiology, population genetics and pharmacogenomics. Its services are available to researchers not only in Trinity College but to other institutions at home and abroad. We provide an automated DNA extraction service purifying large volumes blood (up to 10mL whole blood) and tissue DNA for archival and other purposes. In addition it makes available purified DNA and associated GWAS data from 2000 healthy donors for research use. A key requirement for reliable downstream use of DNA is purity and strand size. The quality of DNA in blood and tissue deteriorates upon storage without purification even at -80 degrees C. We ensure rapid turnaround of biological samples through automated extraction using the Qiagen Autopure system based on optimized ''salting out'' chemistry. The purified DNA sample may then be stored safely at -20 degrees C without deterioration thus freeing up valuable -80 degree C freezer space and the associated capital and maintenance cost as well as security and lab space provision. Automated DNA extraction is particularly suitable for high-throughput sample processing called for in epidemiological studies or simply for clearing sample inventory backlogs. The Trinity Biobank distributes control DNA to researchers as part of its remit to enhance the level of research activity and to synergize molecular medicine research nationally and internationally. The buffy coat collection has been made possible with the cooperation of the Irish Blood Transfusion Service (IBTS). An important requirement to access the collection is that the use of the samples relates only to ethically-approved research and to specifically-nominated research projects. The DNA collection consists of high quality human genomic DNA. Each of the available 2,000 samples is from a single individual and each sample comes with the age and gender data of the donor. The buffy coat sample is derived from the total white cell compliment (50mL buffy coat) of a blood donation (c 400mL). We will endeavor to fulfill samples number requests based on age and gender as best as possible. This collection has also been genotyped using the Affymetrix Genome-Wide Human SNP Array 6.0, featuring 1.8 million genetic markers, including more than 906,600 single nucleotide polymorphisms (SNPs) and more than 946,000 probes for the detection of copy number variation (CNV). The DNA comes available as a 100ng/uL in 100uL of TE Buffer, ie in 10ug amounts in a separate screw-cap ampoule. The ampoules are shipped in 100-tube boxes (Sarstedt). Corresponding plasma (ACD) is also available on request. Genotype data is supplied in PLINK binary PED files format (http://pngu.mgh.harvard.edu/~purcell/plink/ ).

Proper citation: Trinity Biobank (RRID:SCR_013279) Copy   

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http://bbmri-eric.eu

BBMRI is a pan-European and internationally broadly accessible research infrastructure and a network of existing and de novo biobanks and biomolecular resources. The infrastructure will include samples from patients and healthy persons, representing different European populations (with links to epidemiological and health care information), molecular genomic resources and biocomputational tools to optimally exploit this resource for global biomedical research. During the past 3 years BBMRI has grown into a 53-member consortium with over 280 associated organizations (largely biobanks) from over 30 countries, making it the largest research infrastructure project in Europe. During the preparatory phase the concept of a functional pan-European biobank was formulated and has now been presented to Member States of the European Union and for associated states for approval and funding. BBMRI will form an interface between specimens and data (from patients and European populations) and top-level biological and medical research. This can only be achieved through a distributed research infrastructure with operational units in all participating Member States. BBMRI will be implemented under the ERIC (European Research Infrastructure Consortium) legal entity. BBMRI-ERIC foresees headquarters (central coordination) in Graz, Austria, responsible for coordination of the activities of National Nodes established in participating countries. BBMRI is in the process of submitting its application to the European Commission for a legal status under the ERIC regulation, with an expected start date at the end of 2011. Major synergism, gain of statistical power and economy of scale will be achieved by interlinking, standardizing and harmonizing - sometimes even just cross-referencing - a large variety of well-qualified, up-to date, existing and de novo national resources. The network should cover (1) major European biobanks with blood, serum, tissue or other biological samples, (2) molecular methods resource centers for human and model organisms of biomedical relevance, (3) and biocomputing centers to ensure that databases of samples in the repositories are dynamically linked to existing databases and to scientific literature as well as to statistical expertise. Catalog of European Biobanks www.bbmriportal.eu Username: guest / Password: catalogue The catalogue is intended to be used as a reference for scientists seeking information about biological samples and data suitable for their research. The BBMRI catalogue of European Biobanks provides a high-level description of Europe''s biobanks characteristics using a portal solution managing metadata and aggregate data of biobanks. The catalogue can be queried by country, by biobank, by ICD-groups, by specimen types, by specific strengths, by funding and more. A search function is available for all data.

Proper citation: Biobanking and Biomolecular Resources Research Infrastructure (BBMRI) (RRID:SCR_004226) Copy   

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http://www.medunigraz.at/en/biobank

Biobank Graz is a non-profit central Medical University of Graz (MUG) service facility that provides the logistics and infrastructure to optimally support MUG research teams in the collection, processing and storage of biological samples and their associated data. In the course of this, special attention is given to sample and data quality and to the protection of the individual rights of patients. Samples from selected patients at the Graz LKH-University Clinical Centre, who have signed an informed consent declaration, are deposited in Biobank Graz. This means that excess tissue and blood samples are collected and placed in storage. The samples are harvested in the course of routine interventions undertaken by the different departments and institutes of the Graz LKH-University Clinical Centre and approved for use in research projects only after the completion of all necessary laboratory and histopathological analyses. No additional material is removed: in other words, there are no associated drawbacks whatsoever for the patients involved. Biobank Graz operates a quality management system according to ISO 9001:2008 and offers the following services for the processing and storage of biological samples and the handling of data: * Consistently high sample quality through the processing of samples using standardized methods in accordance with written working instructions (SOPs) * Efficient use of resources through the building of shared infrastructure and the development of optimized processes * A high degree of reliability provided by the storage of samples in 24/7 - monitored storage systems. * Processing and storage of all data in accordance with data protection legislation. Biobank Graz comprises both population-based and disease-focused collections of biological materials. It currently contains approx. 3.8 mio samples from approx. 1.2 mio patients representing a nonselected patient group characteristic of central Europe. Because the Institute of Pathology was, until 2003, the exclusive pathology service provider for major parts of the province of Styria, including its capital Graz (population approx. 1.2 mio people), samples from all human diseases, treated by surgery or diagnosed by biopsy, are included in the collection at their natural frequency of occurrence and thus represent cancers and non-cancerous diseases from all organs, and from all age groups. The scientific value of the existing tissue collection is, thus, not only determined by its size and technical homogeneity (all samples have been processed in a single institute under constant conditions for more than 20 years), but also by its population-based character. These features provide ideal opportunities for epidemiological studies and allow the validation of biomarkers for the identification of specific diseases and determination of their response to treatment. Prospectively collected tissues, blood samples and clinical data comprise, on the one hand, randomly selected samples from all diseases and patient groups to provide sufficient numbers of samples for the evaluation of the disease-specificity of any gene or biomarker. On the other hand, Biobank Graz adopts a disease-focused approach for selected diseases (such as breast, colon and liver cancers as well as some metabolic diseases) through the collection of a range of different human biological samples of highest quality and detailed clinical follow-up data. Graz Medical University established the Biobank to provide improved and sustainable access to biological samples and related (clinical) data both for its own academic research and for external research projects of academic and industrial partners. It is a major interest of the university to initiate co-operative research projects. Biological samples and data are available to external institutions performing high-quality research projects which comply with the Biobank''s ethical and legal framework according to the access rules (Contact: COO Karine Sargsyan, MD, PhD).

Proper citation: Biobank Graz (RRID:SCR_004245) Copy   

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http://www.med.unc.edu/bric/ideagroup/free-softwares/unc-infant-0-1-2-atlases

3 atlases dedicated for neonates, 1-year-olds, and 2-year-olds. Each atlas comprises a set of 3D images made up of the intensity model, tissue probability maps, and anatomical parcellation map. These atlases are constructed with the help of state-of-the-art infant MR segmentation and groupwise registration methods, on a set of longitudinal images acquired from 95 normal infants (56 males and 39 females) at neonate, 1-year-old, and 2-year-old.

Proper citation: UNC Infant 0-1-2 Atlases (RRID:SCR_002569) Copy   

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http://cmrm.med.jhmi.edu/cmrm/atlas/human_data/file/JHUtemplate_newuser.html

DTI white matter atlases with different data sources and different image processing. These include single-subject, group-averaged, B0 correction, processed atlases (White Matter Parcellation Map, Tract-probability maps, Conceptual difference between the WMPM and tract-probability maps), and linear or non-linear transformation for automated white matter segmentation. # Adam single-subject white matter atlas (old version): These are electronic versions of atlases published in Wakana et al, Radiology, 230, 77-87 (2004) and MRI Atlas of Human White Matter, Elsevier. ## Original Adam Atlas: 256 x 256 x 55 (FOV = 246 x 246 mm / 2.2 mm slices) (The original matrix is 96x96x55 (2.2 mm isotropic) which is zerofilled to 256 x 256 ## Re-sliced Adam Atlas: 246 x 246 x 121 (1 mm isotropic) ## Talairach Adam: 246 x 246 x 121 (1 mm isotropic) # New Eve single-subject white matter atlas: The new version of the single-subject white matter atlas with comprehensive white matter parcellation. ## MNI coordinate: 181 x 217 x 181 (1 mm isotropic) ## Talairach coordinate: 181 x 217 x 181 (1 mm isotropic) # Group-averaged atlases: This atlas was created from their normal DTI database (n = 28). The template was MNI-ICBM-152 and the data from the normal subjects were normalized by affine transformation. Image dimensions are 181x217x181, 1 mm isotropic. There are two types of maps. The first one is the averaged tensor map and the second one is probabilistic maps of 11 white matter tracts reconstructed by FACT. # ICBM Group-averaged atlases: This atlas was created from ICBM database. All templates follow Radiology convention. You may need to flip right and left when you use image registration software that follows the Neurology convention.

Proper citation: DTI White Matter Atlas (RRID:SCR_005279) Copy   

•   Source: SciCrunch Registry

http://www.cnsforum.com/educationalresources/imagebank/

A collection of downloadable central nervous system (CNS) images for teaching, presentations, articles, and other purposes. The following major categories of images are as follows: Brain anatomy, Brain physiology, Anxiety, Depression, Schizophrenia, Dementia, Parkinson's disease, Stroke, and Others.

Proper citation: CNSforum: Image Bank (RRID:SCR_002718) Copy   

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http://sumsdb.wustl.edu/sums/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on May 11, 2016. Repository of brain-mapping data (surfaces and volumes; structural and functional data) derived from studies including fMRI and MRI from many laboratories, providing convenient access to a growing body of neuroimaging and related data. WebCaret is an online visualization tool for viewing SumsDB datasets. SumsDB includes: * data on cerebral cortex and cerebellar cortex * individual subject data and population data mapped to atlases * data from FreeSurfer and other brainmapping software besides Caret SumsDB provides multiple levels of data access and security: * Free (public) access (e.g., for data associated with published studies) * Data access restricted to collaborators in different laboratories * Owner-only access for work in progress Data can be downloaded from SumsDB as individual files or as bundles archived for offline visualization and analysis in Caret WebCaret provides online Caret-style visualization while circumventing software and data downloads. It is a server-side application running on a linux cluster at Washington University. WebCaret "scenes" facilitate rapid visualization of complex combinations of data Bi-directional links between online publications and WebCaret/SumsDB provide: * Links from figures in online journal article to corresponding scenes in WebCaret * Links from metadata in WebCaret directly to relevant online publications and figures

Proper citation: SumsDB (RRID:SCR_002759) Copy   

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http://cgap.nci.nih.gov/

Project to determine the gene expression profiles of normal, precancer, and cancer cells, whose generated resources are available to the cancer community. Interconnected modules provide access to all CGAP data, bioinformatic analysis tools, and biological resources allowing the user to find in silico answers to biological questions in a fraction of the time it once took in the laboratory. * Genes * Tissues * Pathways * RNAi * Chromosomes * SAGE Genie * Tools

Proper citation: Cancer Genome Anatomy Project (RRID:SCR_003072) Copy   

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http://www.loni.usc.edu/BIRN/Projects/Mouse/

Animal model data primarily focused on mice including high resolution MRI, light and electron microscopic data from normal and genetically modified mice. It also has atlases, and the Mouse BIRN Atlasing Toolkit (MBAT) which provides a 3D visual interface to spatially registered distributed brain data acquired across scales. The goal of the Mouse BIRN is to help scientists utilize model organism databases for analyzing experimental data. Mouse BIRN has ended. The next phase of this project is the Mouse Connectome Project (https://www.nitrc.org/projects/mcp/). The Mouse BIRN testbeds initially focused on mouse models of neurodegenerative diseases. Mouse BIRN testbed partners provide multi-modal, multi-scale reference image data of the mouse brain as well as genetic and genomic information linking genotype and brain phenotype. Researchers across six groups are pooling and analyzing multi-scale structural and functional data and integrating it with genomic and gene expression data acquired from the mouse brain. These correlated multi-scale analyses of data are providing a comprehensive basis upon which to interpret signals from the whole brain relative to the tissue and cellular alterations characteristic of the modeled disorder. BIRN's infrastructure is providing the collaborative tools to enable researchers with unique expertise and knowledge of the mouse an opportunity to work together on research relevant to pre-clinical mouse models of neurological disease. The Mouse BIRN also maintains a collaborative Web Wiki, which contains announcements, an FAQ, and much more.

Proper citation: Mouse Biomedical Informatics Research Network (RRID:SCR_003392) Copy   

•   Source: SciCrunch Registry

http://www.med.umkc.edu/psychiatry/nbtb/

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 31, 2016. The UMKC Neuroscience Brain Tissue Bank and Research Laboratory has been established to obtain, process, and distribute human brain tissue to qualified scientists and clinicians dedicated to neuroscience research. No other living organ approaches the human brain in complexity or capacity. Healthy, it astounds and inspires miracles. Diseased, it confounds and diminishes hope. The use of human brain tissue for research will provide insight into the anatomical and neurochemical aspects of diseased and non-diseased brains. While animal models are helpful and necessary in understanding disease, certain disorders can be more efficiently studied using human brain tissue. Also, modern research techniques are often best applied to human tissue. We also need samples of brain tissue that have not been affected by disease. They help us to compare a 'normal' brain with a diseased one. Also, we have a critical need for brain donations from relatives who have genetically inherited disorders. Tissue preparation consists of fresh quick-frozen tissue blocks or coronal slices (nitrogen vapor frozen; custom dissection of specific anatomic regions) or formalin-fixed coronal slices (custom dissection of specific anatomic regions).

Proper citation: UMKC Neuroscience Brain Tissue Bank and Research Laboratory (RRID:SCR_005148) Copy   

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http://en.wikibooks.org/wiki/MINC/Atlases

A linear average model atlas produced by the International Consortium for Brain Mapping (ICBM) project. A set of full- brain volumetric images from a normative population specifically for the purposes of generating a model were collected by the Montreal Neurological Institute (MNI), UCLA, and University of Texas Health Science Center at San Antonio Research Imaging Center (RIC). 152 new subjects were scanned using T1, T2 and PD sequences using a specific protocol. These images were acquired at a higher resolution than the original average 305 data and exhibit improved contrast due predominately to advances in imaging technology. Each individual was linearly registered to the average 305 and a new model was formed. In total, three models were created at the MNI, the ICBM152_T1, ICBM152_T2 and ICBM152_PD from 152 normal subjects. This resulting model is now known as the ICBM152 (although the model itself has not been published). One advantage of this model is that it exhibits better contrast and better definition of the top of the brain and the bottom of the cerebellum due to the increased coverage during acquisition. The entirely automatic analysis pipeline of this data also included grey/white matter segmentation via spatial priors. The averaged results of these segmentations formed the first MNI parametric maps of grey and white matter. The maps were never made publicly available in isolation but have formed parts of other packages for some time including SPM, FSL AIR and as models of grey matter for EEG source location in VARETTA and BRAINWAVE. Again, as these models are an approximation of Talairach space, there are differences in varying areas, to continue our use of origin shift as an example, the ICBM models are approximately 152: +3.5mm in Z and +-co-ordinate -3.5mm and 2.0mm in Y as compared to the original Talairach origin. In addition to the standard analysis performed on the ICBM data, 64 of the subjects data were segmented using model based segmentation. 64 of the original 305 were manually outlined and a resulting parametric VOI atlas built. The native data from these acquisitions was 256x256 with 1mm slices. The final image resolution of this data was 181x217x181 with 1mm isotropic voxels. Refer to the ICBM152 NonLinear if you are fitting an individual to model and do not care about left/right comparisons. A short history of the various atlases that have been produced at the BIC (McConnell Brain Imaging Center, Montreal Neurological Institute) is provided.

Proper citation: MINC/Atlases (RRID:SCR_005281) Copy   

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http://headit.ucsd.edu

Platform for sharing, download, and re-analysis or meta-analysis of sophisticated, fully annotated, human electrophysiological data sets. It uses EEG Study Schema (ESS) files to provide task, data collection, and subject metadata, including Hierarchical Event Descriptor (HED) tag descriptions of all identified experimental events. Visospatial task data also available from, http://sccn.ucsd.edu/eeglab/data/headit.html: A 238-channel, single-subject EEG data set recorded at the Swartz Center, UCSD, by Arnaud Delorme, Julie Onton, and Scott Makeig is al.

Proper citation: HeadIT (RRID:SCR_005657) Copy   

•   Source: SciCrunch Registry

http://www.cvrgrid.org/

Infrastructure for sharing cardiovascular data and data analysis tools. Human ExVivo heart data set and canine ExVivo normal and failing heart data sets are available. Canine hearts atlas and human InVivo atlases are available.

Proper citation: CardioVascular Research Grid (CVRG) (RRID:SCR_004472) Copy   

•   Source: SciCrunch Registry

http://stemcellcommons.org/

Open source environment for sharing, processing and analyzing stem cell data bringing together stem cell data sets with tools for curation, dissemination and analysis. Standardization of the analytical approaches will enable researchers to directly compare and integrate their results with experiments and disease models in the Commons. Key features of the Stem Cell Commons * Contains stem cell related experiments * Includes microarray and Next-Generation Sequencing (NGS) data from human, mouse, rat and zebrafish * Data from multiple cell types and disease models * Carefully curated experimental metadata using controlled vocabularies * Export in the Investigation-Study-Assay tabular format (ISA-Tab) that is used by over 30 organizations worldwide * A community oriented resource with public data sets and freely available code in public code repositories such as GitHub Currently in development * Development of Refinery, a novel analysis platform that links Commons data to the Galaxy analytical engine * ChIP-seq analysis pipeline (additional pipelines in development) * Integration of experimental metadata and data files with Galaxy to guide users to choose workflows, parameters, and data sources Stem Cell Commons is based on open source software and is available for download and development.

Proper citation: Stem Cell Commons (RRID:SCR_004415) Copy   

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http://umcd.humanconnectomeproject.org

Web-based repository and analysis site for connectivity matrices that have been derived from neuroimaging data including different imaging modalities, subject groups, and studies. Users can analyze connectivity matrices that have been shared publicly and upload their own matrices to share or analyze privately.

Proper citation: USC Multimodal Connectivity Database (RRID:SCR_012809) Copy   

•   Source: SciCrunch Registry

http://sourceforge.net/projects/mutascope/

Software suite to analyze data from high throughput sequencing of PCR amplicons, with an emphasis on normal-tumor comparison for the accurate and sensitive identification of low prevalence mutations.

Proper citation: Mutascope (RRID:SCR_001265) Copy   

•   Source: SciCrunch Registry