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http://gmod.org/wiki/Apollo

A standalone Java application with a GUI (graphical user interface) for editing genome annotations. Like GBrowse, it allows users to scroll and zoom in on areas of interest in a sequence; authorized users can edit annotations and write the changes back to the underlying database. Apollo can run off GFF3 or a Chado database, and it can also integrate with remote services, such as BLAST and Primer BLAST analyses.

Proper citation: Apollo (RRID:SCR_001936) Copy   

•   Source: SciCrunch Registry

http://cancergenome.nih.gov/

Project exploring the spectrum of genomic changes involved in more than 20 types of human cancer that provides a platform for researchers to search, download, and analyze data sets generated. As a pilot project it confirmed that an atlas of changes could be created for specific cancer types. It also showed that a national network of research and technology teams working on distinct but related projects could pool the results of their efforts, create an economy of scale and develop an infrastructure for making the data publicly accessible. Its success committed resources to collect and characterize more than 20 additional tumor types. Components of the TCGA Research Network: * Biospecimen Core Resource (BCR); Tissue samples are carefully cataloged, processed, checked for quality and stored, complete with important medical information about the patient. * Genome Characterization Centers (GCCs); Several technologies will be used to analyze genomic changes involved in cancer. The genomic changes that are identified will be further studied by the Genome Sequencing Centers. * Genome Sequencing Centers (GSCs); High-throughput Genome Sequencing Centers will identify the changes in DNA sequences that are associated with specific types of cancer. * Proteome Characterization Centers (PCCs); The centers, a component of NCI's Clinical Proteomic Tumor Analysis Consortium, will ascertain and analyze the total proteomic content of a subset of TCGA samples. * Data Coordinating Center (DCC); The information that is generated by TCGA will be centrally managed at the DCC and entered into the TCGA Data Portal and Cancer Genomics Hub as it becomes available. Centralization of data facilitates data transfer between the network and the research community, and makes data analysis more efficient. The DCC manages the TCGA Data Portal. * Cancer Genomics Hub (CGHub); Lower level sequence data will be deposited into a secure repository. This database stores cancer genome sequences and alignments. * Genome Data Analysis Centers (GDACs) - Immense amounts of data from array and second-generation sequencing technologies must be integrated across thousands of samples. These centers will provide novel informatics tools to the entire research community to facilitate broader use of TCGA data. TCGA is actively developing a network of collaborators who are able to provide samples that are collected retrospectively (tissues that had already been collected and stored) or prospectively (tissues that will be collected in the future).

Proper citation: The Cancer Genome Atlas (RRID:SCR_003193) Copy   

•   Source: SciCrunch Registry

http://www.sanger.ac.uk/resources/software/dnaplotter/

Software application used to generate images of circular and linear DNA maps to display regions and features of interest. The images can be inserted into a document or printed out directly. As this uses Artemis it can read in the common file formats EMBL, GenBank and GFF3.

Proper citation: DNAPlotter (RRID:SCR_005006) Copy   

•   Source: SciCrunch Registry

http://ki.se/en/meb/twingene-and-genomeeutwin

In collaboration with GenomeEUtwin, the TwinGene project investigates the importance of quantitative trait loci and environmental factors for cardiovascular disease. It is well known that genetic factors are of considerable importance for some familial lipid syndromes and that Type A Behavior pattern and increased lipid levels infer increased risk for cardiovascular disease. It is furthermore known that genetic factors are of importance levels of blood lipid biomarkers. The interplay of genetic and environmental effects for these risk factors in a normal population is less well understood and virtually unknown for the elderly. In the TwinGene project twins born before 1958 are contacted to participate. Health and medication data are collected from self-reported questionnaires, and blood sampling material is mailed to the subject who then contacts a local health care center for blood sampling and a health check-up. In the simple health check-up, height, weight, circumference of waist and hip, and blood pressure are measured. Blood is sampled for DNA extraction, serum collection and clinical chemistry tests of C-reactive protein, total cholesterol, triglycerides, HDL and LDL cholesterol, apolipo��protein A1 and B, glucose and HbA1C. The TwinGene cohort contains more than 10000 of the expected final number of 16000 individuals. Molecular genetic techniques are being used to identify Quantitative Trait Loci (QTLs) for cardiovascular disease and biomarkers in the TwinGene participants. Genome-wide linkage and association studies are ongoing. DZ twins have been genome-scanned with 1000 STS markers and a subset of 300 MZ twins have been genome-scanned with Illumina 317K SNP platform. Association of positional candidate SNPs arising from these genomscans are planned. The TwinGene project is associated with the large European collaboration denoted GenomEUtwin (www.genomeutwin.org, see below) which since 2002 has aimed at gathering genetic data on twins in Europe and setting up the infrastructure needed to enable pooling of data and joint analyses. It has been the funding source for obtaining the genome scan data. Types of samples: * EDTA whole blood * DNA * Serum Number of sample donors: 12 044 (sample collection completed)

Proper citation: KI Biobank - TwinGene (RRID:SCR_006006) Copy   

•   Source: SciCrunch Registry

https://github.com/adigenova/fast-sg

Algorithm for alignment-free scaffolding graph construction from short or long reads. It allows the reuse of efficient algorithms designed for short read data and permits the definition of novel modular hybrid assembly pipelines.

Proper citation: Fast-SG (RRID:SCR_015934) Copy   

•   Source: SciCrunch Registry

https://www.ncbi.nlm.nih.gov/sites/batchentrez

Software program for loading numbers of genome records. Allows the retrieval of a large number of nucleotide sequences or protein sequences, in a batch mode, by importing a file containing a list of the desired GI or accession numbers.

Proper citation: Batch Entrez (RRID:SCR_016634) Copy   

•   Source: SciCrunch Registry

http://www.einstein.yu.edu/departments/genetics/resources/molecular-cytogenetics-core.aspx

Core provides tools for preparation of human and murine samples suitable for molecular genetic and cytogenetic analysis of entire genome. These tools include establishment of EBV transformed cell lines; isolation of DNA and mRNA from variety of tissue culture samples as well as primary biopsies; preparation of metaphase chromosomes suitable for fluorescence in situ hybridization (FISH) and Spectral Karyotyping (SKY) or whole chromosome paints for human and mouse genome. Core personnel is trained to hybridize commercial probes and to designed locus specific probes for regions of interest to investigators. All probes are custom designed and in house generated.

Proper citation: Albert Einstein College of Medicine Molecular Cytogenetics Core Facility (RRID:SCR_017815) Copy   

•   Source: SciCrunch Registry

http://hihg.med.miami.edu/cgt/gene-expression

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 27,2025. CGT gene expression core utilizes Affymetrix GeneChip Arrays and Illumina BeadChips to identify gene expression variation in single genes, targeted set of genes, or entire genomes. Affymetrix GeneChip Arrays Human Gene ST,Human Transcriptome Array 2.0, Human Exon ST, Human miRNA, Illumina Expression, HumanHT-12 v4 BeadChip.

Proper citation: University of Miami Miller School of Medicine Gene Expression Core Facility (RRID:SCR_017825) Copy   

•   Source: SciCrunch Registry

http://htbc.stanford.edu

Core provides fully automated high throughput screening (HTS) of Compound Libraries (130,000+ compounds) for both enzyme/protein-based assays and cell-based assays, using Caliper Life Sciences Staccato system;Genomic siRNA screening with siARRAY whole human genome siRNA library from Dharmacon targeting 21,000 genes, using Agilent Bravo system;High-Content Screening using ImageXpress Micro automated fluorescent microscope with live cell, bright field, phase contrast and integrated plate handling with Thermo Catalyst CRS, and image analysis using MetaXpress software;High Throughput Molecular Biology reagents and services, including access to cDNA libraries (Human ORFeome collection, 15,000 genes) and 96 and 384-well bead clean-ups and PCR setup (Biomek FX and Agilent Bravo), and other automation steps in collaboration with SFGF;High-throughput assay development assistance with cell culture, experiment design, robotic programming and Standard Operating Procedure drafting;Screening data analysis assistance with protocols, hit determination and structure activity analyses using MDL chemical database ISIS/HOST, Plate Manager, Assay Explorer and Report Manager. Use of microplate reader detection systems, including Tecan Infinite M1000 and Infinite M1000 PRO and Molecular Devices Analyst GT for fluorescence; fluorescence polarization; time-resolved fluorescence; absorbance and luminescence (with injectors and AlphaScreen); and Flexstation II 384, for kinetic fluorescence reads to measure calcium mobilization and ion channels.Use of liquid-handling robots, including Sciclone ALH3000 (96- and 384-well pipetting), Agilent Bravo (96- and 384-well pipetting), Velocity11 VPrep (96-well pipetting), Bio-Tek plate washers/dispensers, Matrix Wellmate and Titertek/Labsystems Multidrop microplate dispensers, and Velocity11 PlateLoc plate heat sealer;Training for most of these services.

Proper citation: Stanford University School of Medicine High Throughput Bioscience Center Core Facility (RRID:SCR_017794) Copy   

•   Source: SciCrunch Registry

https://med.nyu.edu/research/scientific-cores-shared-resources/genome-technology-center

Core provides range of services related to genome, epigenome, and transcriptome analysis. Offers technologies including Illumina deep sequencing and sample preparation for variety of applications, including DNA and RNA sequencing (DNA- and RNA-seq), exome sequencing, targeted capture, chromatin immunoprecipitation sequencing (ChIP-seq), methylation sequencing (Methyl-seq), metagenomics, and many others;Automation of Illumina library and targeted capture preps, including 16S ribosomal RNA (rRNA) sequencing;Oxford Nanopore sequencing (long reads);Bio-Rad Droplet Digita polymerase chain reaction (PCR);Nanostring nCounter;Single-cell RNA- and DNA-seq using the C1 Auto Prep System from Fluidigm, and 10x Genomics Chromium System.Provides expertise on strategies to achieve research goals in any field related to genomics, and can tailor bioinformatics analysis to individual project. If you supply us with nucleic acids, we can perform every step required to help you achieve your desired results.

Proper citation: New York University School of Medicine Langone Health Genome Technology Center Core Facility (RRID:SCR_017929) Copy   

•   Source: SciCrunch Registry

http://mousebiology.org

Core located on campus of UC Davis, providing fully customized support for scientific research using genetically altered mice. Provides access to develop, plan, execute, and analyze research project involving genetically-altered mice. Provides description of project, including alternative approaches, accurate timelines, and cost estimates.Provides regular and informative communication throughout project, including email updates on completion of each milestone. Project progress can be followed at each stage by viewing detailed information anytime by accessing our online and secure project tracking system (PTS) available 24 hours a day.

Proper citation: University of California-Davis Mouse Biology Program CRISPR Based Genome Editing Service Core Facility (RRID:SCR_017851) Copy   

•   Source: SciCrunch Registry

https://grcf.jhmi.edu/

Established to produce immortalized cell lines from human blood (EBV transformations). Offers genomics applications for single cells, including RNA-seq, gene expression profiling by qPCR and DNA amplification for whole-genome or targeted (exome or PCR-based analysis) through 10x Genomics Chromium platform (similar to Drop Seq). Offers custom genotyping to analyze short tandem repeats, variable number tandem repeats and single nucleotide polymorphisms.

Proper citation: Johns Hopkins University School of Medicine Genetic Resources Core Facility (RRID:SCR_018669) Copy   

•   Source: SciCrunch Registry

https://broadinstitute.github.io/warp/docs/Pipelines/SlideTags_Pipeline/README

Software pipeline as open-source, cloud-optimized workflow for processing spatial transcriptomics data. It supports data derived from spatially barcoded sequencing technologies, including Slide-tags-based single-molecule profiling. The pipeline processes raw sequencing data into spatially resolved gene expression matrices, ensuring accurate alignment, spatial positioning, and quantification.

Proper citation: SlideTags.wdl (RRID:SCR_027567) Copy   

•   Source: SciCrunch Registry

https://einsteinmed.edu/research/shared-facilities/cores/53/epigenomics/

Part of Einstein Center for Epigenomics and Illumina CSPro (certified service provider) laboratory, offers massively-parallel sequencing (MPS) including fully-automated library preparation, quality control and assurance, and number of assays to study the genome/epigenome. Data analytical services are provided by Computational Genomics Facility.

Proper citation: Albert Einstein College of Medicine Epigenomics Shared Core Facility (RRID:SCR_023284) Copy   

•   Source: SciCrunch Registry

https://github.com/huangnengCSU/compleasm

Software genome completeness evaluation tool based on miniprot.

Proper citation: compleasm (RRID:SCR_026370) Copy   

•   Source: SciCrunch Registry

https://github.com/YongyiLuo98/BVSim

Software package provides several functions and parameters for simulating genetic variations. Benchmarking variation simulator mimicking human variation spectrum.

Proper citation: BVSim (RRID:SCR_026926) Copy   

•   Source: SciCrunch Registry