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http://biomath.med.uth.gr

Software application for performing genome scan meta-analysis, a quantitative method to identify genetic regions (bins) with consistently increased linkage score across multiple genome scans, and for testing the heterogeneity of the results of each bin across scans. The program provides as an output the average of ranks and three heterogeneity statistics, as well as corresponding significance levels. (entry from Genetic Analysis Software)

Proper citation: HEGESMA (RRID:SCR_013304) Copy   

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http://www.pypop.org/

Open-source software pipeline for population genomics. Designed for processing genotype and allele data and running population genetic analyses, including conformity to Hardy-Weinberg expectations; tests for balancing or directional selection; estimates of haplotype frequencies and measures and tests of significance for linkage disequilibrium.

Proper citation: PyPop (RRID:SCR_013425) Copy   

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http://www.multifactordimensionalityreduction.org/

Software application that is a data mining strategy for detecting and characterizing nonlinear interactions among discrete attributes (e.g. SNPs, smoking, gender, etc.) that are predictive of a discrete outcome (e.g. case-control status). The MDR software combines attribute selection, attribute construction and classification with cross-validation to provide a powerful approach to modeling interactions. (entry from Genetic Analysis Software)

Proper citation: MDR (RRID:SCR_013427) Copy   

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http://lbm.ab.a.u-tokyo.ac.jp/~iwata/antmap/

Software application based on the Ant Colony Optimization to solve the special case of the traveling salesman problem of ordering markers when the number of loci is large. ANYMAP performs segregation test, linkage grouping and locus ordering, and constructs a linkage map rapidly. (entry from Genetic Analysis Software)

Proper citation: ANTMAP (RRID:SCR_013426) Copy   

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http://www.gridqtl.org.uk/

Publicly available Web-based application that can perform QTL mapping on a variety of population types. GridQTL will extend the functionality of QTLExpress by adding new and advanced approaches for modelling QTL analysis in simple and complex populations. These new methods will be available on a Grid system that will offer flexible workflow management, resource allocation, data persistence, detached execution of simulations and the scalability required for the increase in data volume, data sources and complexity required by the new models. (entry from Genetic Analysis Software)

Proper citation: GRIDQTL (RRID:SCR_013397) 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://vipbg.vcu.edu/vipbg/trimhap//

Software application for linkage disequilibrium mapping based on ancestral founder haplotypes. Method uses haplotype data from general pedigrees. (entry from Genetic Analysis Software)

Proper citation: TRIMHAP (RRID:SCR_013512) Copy   

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http://www.som.soton.ac.uk/research/geneticsdiv/epidemiology/chromscan/

A statistical based program for association mapping of disease genes. It utilises the Malecot model and the linkage disequilibrium (LD) map for the candidate region to analyse the genotypes derive from large sample of matched cases and controls. (entry from Genetic Analysis Software)

Proper citation: CHROMSCAN (RRID:SCR_013131) Copy   

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http://mayoresearch.mayo.edu/mayo/research/schaid_lab/software.cfm

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 24,2023. Software application to compute composite measures of linkage disequilibrium, their variances and covariances, and statistical tests, for all pairs of alleles from two loci when linkage phase is unkown. An extension of Weir and Cockerham (1989) to apply to multi-allelic loci. (entry from Genetic Analysis Software)

Proper citation: COMPOSITELD (RRID:SCR_013132) Copy   

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http://faculty.washington.edu/eathomp/Anonftp/PANGAEA/BOREL/

Software application for inference of genealogical relationships from genetic data, including sibship inference.

Proper citation: BOREL (RRID:SCR_013135) Copy   

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http://mayoresearch.mayo.edu/mayo/research/schaid_lab/software.cfm

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 24,2023. Software application for statistical methods for disease and genetic marker associations using cases and their parents. These methods include an extension of the transmission/disequilibrium test (TDT) for multiple marker alleles, as well as additional general tests sensitive to associations that depend on dominant or recessive genetic mechanisms. (entry from Genetic Analysis Software)

Proper citation: GASSOC (RRID:SCR_013136) Copy   

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http://www.bio.unc.edu/faculty/vision/lab/mappop/

Software application that selects high resolution mapping subsamples and performs bin mapping (entry from Genetic Analysis Software)

Proper citation: MAPPOP (RRID:SCR_013490) Copy   

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http://dlin.web.unc.edu/software/SNPMStat/

A command-line program for the statistical analysis of SNP-disease association in case-control/cohort/cross-sectional studies with potentially missing genotype data. SNPMStat allows the user to estimate or test SNP effects and SNP-environment interactions by maximizing the (observed-data) likelihood that properly accounts for phase uncertainty, study design and gene-environment dependence. For SNPs without missing data, the program performs the standard association analysis. For typed SNPs with missing data or untyped SNPs, the program performs the maximum-likelihood analysis. (entry from Genetic Analysis Software)

Proper citation: SNPMSTAT (RRID:SCR_013339) Copy   

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http://www.cbil.ece.vt.edu/ResearchOngoingSNP.htm

Software application (entry from Genetic Analysis Software)

Proper citation: MECPM (RRID:SCR_013341) Copy   

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http://www.bios.unc.edu/~lin/software/MAOS/

Software application that implements valid and efficient statistical methods for meta-analysis of genomewide association studies with overlapping subjects. The current release performs logistic regression analysis of individual level data under the additive mode of inheritance. Data from genome-wide association studies are often analyzed jointly for the purposes of combining information from multiple studies of the same disease or comparing results across different disorders. In many instances, the same subjects appear in multiple studies. Failure to account for overlapping subjects can greatly inflate type I error when combining results from multiple studies of the same disease and can drastically reduce power when comparing results across different disorders. (entry from Genetic Analysis Software)

Proper citation: MAOS (RRID:SCR_013351) Copy   

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http://www.scienceexchange.com/facilities/university-of-utah

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on April 15,2024. Labs and facilities of the University of Utah, which include: Microarray and Genomic Analysis Core Facility, Flow Cytometry Core Facility, Mutation Generation and Detection Facility, and the Transgenic and Gene Targeting Core.

Proper citation: University of Utah Labs and Facilities (RRID:SCR_001042) Copy   

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http://archive.ics.uci.edu/ml/datasets/EEG+Database

Data set from a large study to examine EEG correlates of genetic predisposition to alcoholism. It contains measurements from 64 electrodes placed on the scalp sampled at 256 Hz (3.9-msec epoch) for 1 second. There were two groups of subjects: alcoholic and control. Each subject was exposed to either a single stimulus (S1) or to two stimuli (S1 and S2) which were pictures of objects chosen from the 1980 Snodgrass and Vanderwart picture set. When two stimuli were shown, they were presented in either a matched condition where S1 was identical to S2 or in a non-matched condition where S1 differed from S2. There were 122 subjects and each subject completed 120 trials where different stimuli were shown. The electrode positions were located at standard sites (Standard Electrode Position Nomenclature, American Electroencephalographic Association 1990). Zhang et al. (1995) describes in detail the data collection process. There are three versions of the EEG data set. * The Small Data Set (smni97_eeg_data.tar.gz) contains data for the 2 subjects, alcoholic a_co2a0000364 and control c_co2c0000337. For each of the 3 matching paradigms, c_1 (one presentation only), c_m (match to previous presentation) and c_n (no-match to previous presentation), 10 runs are shown. * The Large Data Set (SMNI_CMI_TRAIN.tar.gz and SMNI_CMI_TEST.tar.gz) contains data for 10 alcoholic and 10 control subjects, with 10 runs per subject per paradigm. The test data used the same 10 alcoholic and 10 control subjects as with the training data, but with 10 out-of-sample runs per subject per paradigm. * The Full Data Set contains all 120 trials for 122 subjects. The entire set of data is about 700 MBytes.

Proper citation: EEG Database (RRID:SCR_001581) Copy   

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

The EBI genomes pages give access to a large number of complete genomes including bacteria, archaea, viruses, phages, plasmids, viroids and eukaryotes. Methods using whole genome shotgun data are used to gain a large amount of genome coverage for an organism. WGS data for a growing number of organisms are being submitted to DDBJ/EMBL/GenBank. Genome entries have been listed in their appropriate category which may be browsed using the website navigation tool bar on the left. While organelles are all listed in a separate category, any from Eukaryota with chromosome entries are also listed in the Eukaryota page. Within each page, entries are grouped and sorted at the species level with links to the taxonomy page for that species separating each group. Within each species, entries whose source organism has been categorized further are grouped and numbered accordingly. Links are made to: * taxonomy * complete EMBL flatfile * CON files * lists of CON segments * Project * Proteomes pages * FASTA file of Proteins * list of Proteins

Proper citation: EBI Genomes (RRID:SCR_002426) Copy   

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https://clinicaltrials.gov/study/NCT00342927?term=AREA%5BBasicSearch%5D(NIDDK%20endocrine%20and%20diabetes)%20AND%20AREA%5BSponsorSearch%5D(NIDDK)%20AND%20AREA%5BOverallStatus%5D(NOT_YET_RECRUITING%20OR%20RECRUITING%20OR%20ACTIVE_NOT_RECRUITING)&rank=1

Multicenter observational study designed to identify genetic determinants of diabetic nephropathy. It is conducted in eleven U.S. clinical centers and a coordinating center, and with four ethnic groups (European Americans, African Americans, Mexican Americans, and American Indians). Two strategies are used to localize susceptibility genes: a family-based linkage study and a case-control study using mapping by admixture linkage disequilibrium (MALD). In the family-based study, probands with diabetic nephropathy are recruited with their parents and selected siblings. Linkage analyses will be conducted to identify chromosomal regions containing genes that influence the development of diabetic nephropathy or related quantitative traits such as serum creatinine concentration, urinary albumin excretion, and plasma glucose concentrations. Regions showing evidence of linkage will be examined further with both genetic linkage and association studies to identify genes that influence diabetic nephropathy or related traits. Two types of MALD studies are being done. One is a case-control study of unrelated individuals of Mexican American heritage in which both cases and controls have diabetes, but only the case has nephropathy. The other is a case-control study of African American patients with nephropathy (cases) and their spouses (controls) unaffected by diabetes and nephropathy; offspring are genotyped when available to provide haplotype data. The specific goals of this program: * Delineate genomic regions associated with the development and progression of renal disease(s) * Evaluate whether there is a genetic link between diabetic nephropathy and diabetic retinopathy * Improve outcomes * Provide protection for people at risk and slow the progression of renal disease * Help establish a resource for genetic studies of kidney disease and diabetic complications by creating a repository of genetic samples and a database * Encourage studies of the genetics of progressive renal disease

Proper citation: Family Investigation of Nephropathy of Diabetes (RRID:SCR_001525) Copy   

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http://bpg.utoledo.edu/~afedorov/lab/eid.html

Data sets of protein-coding intron-containing genes that contain gene information from humans, mice, rats, and other eukaryotes, as well as genes from species whose genomes have not been completely sequenced. This is a comprehensive and convenient dataset of sequences for computational biologists who study exon-intron gene structures and pre-mRNA splicing. The database is derived from GenBank release 112, and it contains protein-coding genes that harbor introns, along with extensive descriptions of each gene and its DNA and protein sequences, as well as splice motif information. They have created subdatabases of genes whose intron positions have been experimentally determined. The collection also contains data on untranslated regions of gene sequences and intron-less genes. For species with entirely sequenced genomes, species-specific databases have been generated. A novel Mammalian Orthologous Intron Database (MOID) has been introduced which includes the full set of introns that come from orthologous genes that have the same positions relative to the reading frames.

Proper citation: EID: Exon-Intron Database (RRID:SCR_002469) Copy   

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