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Professional society of genetic counselors that promotes networking, continuing education opportunities, advocacy, and discussion of relevant issues in the field of genetics.
Software package that creates genomic builds, calls SNPs, detects indels, and counts reads from data generated from one or more sequencing runs. In addition, CASAVA automatically generates a range of statistics, such as mean depth and percentage chromosome coverage, to enable comparison with previous builds or other samples. CASAVA analyzes sequencing reads in three stages: * FASTQ file generation and demultiplexing * Alignment to a reference genome * Variant detection and counting
Software for combinatorial polyfunctionality analysis of single cells. It is a statistical framework that enables unbiased analysis of antigen-specific T-cell subsets. It uses a Bayesian hierarchical framework to model all observed cell-subsets and select the most likely to be antigen-specific while regularizing the small cell counts that often arise in multi-parameter space. The model provides a posterior probability of specificity for each cell subset and each sample, which can be used to profile a subject's immune response to external stimuli such as infection or vaccination.
Software application that is a combined functional annotation score of non-synonymous coding variants. A major challenge in interpreting whole-exome data is predicting which of the discovered variants are deleterious or neutral. To address this question in silico, they have developed a score called Combined Annotation scoRing toOL (CAROL), which combines information from two bioinformatics tools: PolyPhen-2 and SIFT, in order to improve the prediction of the effect of non-synonymous coding variants. The combination of annotation tools can help improve automated prediction of whole-genome/exome non-synonymous variant functional consequences. (entry from Genetic Analysis Software) The software should run on any UNIX or GNU/Linux system.
A Perl/C++ software package that provides genome-wide detection of structural variants from next generation paired-end sequencing reads. BreakDancerMax predicts five types of structural variants: insertions, deletions, inversions, inter- and intra-chromosomal translocations from next-generation short paired-end sequencing reads using read pairs that are mapped with unexpected separation distances or orientation. (entry from Genetic Analysis Software)
Freely-accessible auditory databases as well as custom designed modeling and data analysis software tools. A fully functional online auditory modeling environment is also available, as well as downloadable models in several languages. The models cover many aspects of auditory function and at many different levels of detail ranging from multi-compartment celluar models to high-level abstractions of large portions of the auditory pathway. Currently a few models are available that can be run online and others are available for downloading. EarLab also provides custom cross-platform software for creating your own distributed auditory modeling environment, as well as software for analyzing the results from experimentation. A database of auditory modules is available for online use or download for the distributed auditory modeling environment, as well as instructions and specifications for creating your own modules. All these databases and custom software tools can be used in a wide variety of hearing research applications. This unique resource provides a wealth of information on auditory processing in humans and other animals. Mathematical models are also provided.
Software for integrated detection of natural antisense transcripts using strand-specific RNA sequencing data.
THIS RESOURCE IS NO LONGER IN SERVICE, documented August 23, 2016. Obesity e-Lab is a unique, secure environment for producing, sharing, communicating and finding obesity research between epidemiologists, public health researchers and social scientists. Features of e-Lab: - Tools to share: it enables social and biomedical researchers to share data, information and analytical tools for obesity research. First, it will create a portal to provide access to the platform and facilitate social networking. - Navigation tools: Second, it will generate search and navigation tools for researchers in academic, NHS or local government organizations to find data from administrative and secure data services, via social science views of health datasets, and health science views of social datasets. Within the NHS, e-Lab links records from a variety of administrative and health (and social) care sources for broadly-specified obesity research, and make pseudonymised extracts of NHS-linked datasets available via the portal. - Analytical tools: Third, it will develop analytical tools, focused on: i) easy, reliable and privacy-protecting transformation of geo-codes in health records to other geographies and area-based social and economic measures; ii) epidemiological extensions to geographical information systems; iii) growth-standardization of child obesity measures. The tool-building will employ as much existing software as possible, focusing on the provision of simple, intuitive interfaces to proven software to make it easy for social or biomedical researchers to use collaboratively.
Community repository and virtual research environment where scientists can safely publish their workflows and experiment plans, share them with groups and find and use those of others. Workflows, other digital objects and collections (called Packs) can be swapped, sorted and searched. It supports Linked data, has a SPARQL Endpoint and REST API and is based on an open source Ruby on Rails codebase. Scientific workflows in various formats can be uploaded. Specific support is provided for Taverna workflows for which the system displays relevant metadata, components and visual previews, that are retrieved directly from workflow files. Version history for workflows is collected. This feature allows the contributor to keep previous versions of the workflow available, when the latest one is uploaded. This brings additional benefit for the users by allowing them to view the development stages of the workflow towards its latest implementation.
Open-source set of tools to detect and report SNP genotypes, common Copy-Number Polymorphisms (CNPs), and novel, rare, or de novo CNVs in samples processed with the Affymetrix platform. While most of the components of the suite can be run individually (for instance, to only do SNP genotyping), the Birdsuite is especially intended for integrated analysis of SNPs and CNVs.
Database of proteins found in the nucleoli of Arabidopsis, identified through proteomic analysis. The Arabidopsis Nucleolar Protein database (AtNoPDB) provides information on the plant proteins in comparison to human and yeast proteins, and images of cellular localizations for over a third of the proteins. A proteomic analysis was carried out of nucleoli purified from Arabidopsis cell cultures and to date 217 proteins have been identified. Many proteins were known nucleolar proteins or proteins involved in ribosome biogenesis. Some proteins, such as spliceosomal and snRNP proteins, and translation factors, were unexpected. In addition, proteins of unknown function which were either plant-specific or conserved between human and plant, and proteins with differential localizations were identified.
Database providing a systematic and comprehensive view of morphological phenotypes regulated by plant hormones, as well as regulatory genes participating in numerous plant hormone responses. By integrating the data from mutant studies, transgenic analysis and gene ontology annotation, genes related to the stimulus of eight plant hormones were identified, including abscisic acid, auxin, brassinosteroid, cytokinin, ethylene, gibberellin, jasmonic acid and salicylic acid. Another pronounced characteristics of this database is that a phenotype ontology was developed to precisely describe all kinds of morphological processes regulated by plant hormones with standardized vocabularies. To increase the coverage of phytohormone related genes, the database has been updated from AHD to AHD2.0 adding and integrating several pronounced features: (1) added 291 newly published Arabidopsis hormone related genes as well as corrected information (e.g. the arguable ABA receptors) based on the recent 2-year literature; (2) integrated orthologues of sequenced plants in OrthoMCLDB into each gene in the database; (3) integrated predicted miRNA splicing site in each gene in the database; (4) provided genetic relationship of these phytohormone related genes mining from literature, which represents the first effort to construct a relatively comprehensive and complex network of hormone related genes as shown in the home page of our database; (5) In convenience to in-time bioinformatics analysis, they also provided links to a powerful online analysis platform Weblab that they have recently developed, which will allow users to readily perform various sequence analysis with these phytohormone related genes retrieved from AHD2.0; (6) provided links to other protein databases as well as more expression profiling information that would facilitate users for a more systematic analysis related to phytohormone research. Please help to improve the database with your contributions.
A manually curated database of both known and predicted metabolic pathways for the laboratory mouse. It has been integrated with genetic and genomic data for the laboratory mouse available from the Mouse Genome Informatics database and with pathway data from other organisms, including human. The database records for 1,060 genes in Mouse Genome Informatics (MGI) are linked directly to 294 pathways with 1,790 compounds and 1,122 enzymatic reactions in MouseCyc. (Aug. 2013) BLAST and other tools are available. The initial focus for the development of MouseCyc is on metabolism and includes such cell level processes as biosynthesis, degradation, energy production, and detoxification. MouseCyc differs from existing pathway databases and software tools because of the extent to which the pathway information in MouseCyc is integrated with the wealth of biological knowledge for the laboratory mouse that is available from the Mouse Genome Informatics (MGI) database.
R analysis and processing package for Illumina platform Chip-Seq data.
Software package for analysis of large-scale genetic data sets with hundreds of thousands of markers genotyped on thousands of samples. BEAGLE can * phase genotype data (i.e. infer haplotypes) for unrelated individuals, parent-offspring pairs, and parent-offspring trios. * infer sporadic missing genotype data. * impute ungenotyped markers that have been genotyped in a reference panel. * perform single marker and haplotypic association analysis. * detect genetic regions that are homozygous-by-descent in an individual or identical-by-descent in pairs of individuals. Beagle can also be used in conjunction with PRESTO, a program for fast and flexible permutation testing. PRESTO can compute empirical distributions of order statistics, analyze stratified data, and determine significance levels for one-stage and two-stage genetic association studies. BEAGLE is written in Java and runs on any computing platform with a Java version 1.6 interpreter (e.g. Windows, Unix, Linux, Solaris, Mac).
Software package for detecting transposable elements (TEs) insertions and excisions from pooled high-throughput sequencing data.
Software to characterize the genetic variation of alternative splicing using a robust statistical method for detecting splicing quantitative trait loci (sQTLs) from RNA-seq data. It takes into account the individual variation in sequencing coverage and the noise prevalent in RNA-seq data.
A normalization tool for RNA-Seq data, implementing the conditional quantile normalization method.
The In-Vivo Molecular Imaging Laboratory (IMIL) is a MSSM shared resource facility serving the research community of Mount Sinai with equipment and imaging expertise. State-of-the-art bioluminescent as well as fluorescent imaging modalities are supported for in-vivo monitoring of cellular and genetic activity. Investigators are provided with cutting edge imaging technologies as well as analysis techniques. The long-term goal is to establish a comprehensive SRF for in-vivo molecular imaging using micro-MRI, micro-PET and other modalities. IMIL houses a Xenogen IVIS-200 Series imaging system with the integrated fluorescent imaging options. Simultaneous dual reporter in-vivo imaging is possible with bioluminescence and fluorescence probes. The imaging chamber has a gas anesthesia manifold that can accommodate up to 5 mice for simultaneously image acquisition. Selectable field of views allow in-plane (X,Y) imaging resolutions of up to 60-microm. Integrated spectra filters allow for the determination of signal source depth (Z). IMIL will provide data acquisition services as well as analysis. IMIL has a dedicated imaging technologist for data acquisition. Investigators will bring their prepared animal to the lab and an IMIL imaging technologist will assist in sedating the animals and acquire imaging data. Typical imaging sessions last about an hour. Certified users who are trained in the use of the software will be able to perform their own analysis at the console. Usage of the imaging device is charged by the hour ($100/hour). Structural Imaging The IVIS-200 has the built-in capability of obtaining an image of the surface topography of the animal for 2D and 3D localization. If additional true 3D imaging data is required, micro MRI is available through the Imaging Science Laboratories (ISL). Image Analysis The IVIS-200 has an integrated image acquisition and analysis software (Living Image Software 2.50). Comprehensive data quantification is possible with this software. Raw data as well as analyzed results can be electronically transferred to the investigators. Support is also available for additional image analysis such as intermodality coregistration, 3D rendering, and group statistics. Additional software packages include MedX, SPM, Brainvoyager, Analyze, and in-house developed software.
Software package that implements a method for normalization, testing, and false discovery rate estimation for RNA-sequencing data.