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SciCrunch Registry is a curated repository of scientific resources, with a focus on biomedical resources, including tools, databases, and core facilities - visit SciCrunch to register your resource.
Interoperability framework which supports integrative genomics analysis via access to various bioinformatics tools. Rather than performing analyses itself, GenomeSpace acts as a hub for data from supported bioinformatics tools and reformats data and results when necessary.
Proper citation: GenomeSpace (RRID:SCR_014967) Copy
https://github.com/smithlabcode/riborex
Software R package for identification of differential translation from Ribo-seq data. Computational tool for mapping genome wide differences in translation efficiency.
Proper citation: riborex (RRID:SCR_019104) Copy
https://www.cbcb.umd.edu/software/epiviz
Software package as interactive visualization tool for functional genomics data. Interactive visual analytics for functional genomics data.
Proper citation: Epiviz (RRID:SCR_022796) Copy
https://bioconductor.org/packages/release/bioc/html/Maaslin2.html
SoftwareR package that identifies microbial taxa correlated with factors of interest using generalized linear models and mixed models.Used for efficiently determining multivariable association between clinical metadata and microbial meta'omic features.
Proper citation: MaAsLin2 (RRID:SCR_023241) Copy
https://github.com/ParkerLab/ataqv
Software package for QC and visualization of ATAC-seq results. Used to examine aligned reads and report basic metrics, including reads mapped in proper pairs, optical or PCR duplicates, reads mapping to autosomal or mitochondrial references, ratio of short to mononucleosomal fragment counts, mapping quality, various kinds of problematic alignments.
Proper citation: ataqv (RRID:SCR_023112) Copy
https://github.com/fritzsedlazeck/SURVIVOR
Software tool set for simulating and evaluating SVs, merging and comparing SVs within and among samples, and includes various methods to reformat or summarize SVs. Used for for SV simulation, comparison and filtering.
Proper citation: SURVIVOR (RRID:SCR_022995) Copy
https://github.com/marbl/merqury
Software toolkit for reference free quality, completeness, and phasing assessment for genome assemblies. Genome assembly quality evaluation based on k-mers.
Proper citation: Merqury (RRID:SCR_022964) Copy
https://github.com/virajbdeshpande/AmpliconArchitect
Software package designed to call circular DNA from short read WGS data.Used to identify one or more connected genomic regions which have simultaneous copy number amplification and elucidates architecture of amplicon.Used to reconstruct structure of focally amplified regions using whole genome sequencing and validate it extensively on multiple simulated and real datasets, across wide range of coverage and copy numbers.
Proper citation: AmpliconArchitect (RRID:SCR_023150) Copy
https://github.com/genome/bam-readcount
Software tool that runs on BAM or CRAM file and generates low level information about sequencing data at specific nucleotide positions. Its outputs include observed bases, readcounts, summarized mapping and base qualities, strandedness information, mismatch counts, and position within the reads.
Proper citation: bam readcount (RRID:SCR_023653) Copy
https://bioconductor.org/packages/release/bioc/html/oligo.html
Software R package to analyze oligonucleotide arrays at probe level. Supports Affymetrix (CEL files) and NimbleGen arrays (XYS files). Used for annotation of Affymetrix Gene Array data.
Proper citation: Preprocessing tools for oligonucleotide arrays (RRID:SCR_023726) Copy
https://github.com/churchmanlab/genewalk
Software for individual genes functions determination that are relevant in particular biological context and experimental condition. Quantifies similarity between vector representations of gene and annotated GO terms through representation learning with random walks on condition specific gene regulatory network. Similarity significance is determined through comparison with node similarities from randomized networks.
Proper citation: GeneWalk (RRID:SCR_023787) Copy
The NCGC Pharmaceutical Collection (NPC) is a comprehensive, publically-accessible collection of approved and investigational drugs for high-throughput screening that provides a valuable resource for both validating new models of disease and better understanding the molecular basis of disease pathology and intervention. The NPC has already generated several useful probes for studying a diverse cross section of biology, including novel targets and pathways. NCGC provides access to its set of approved drugs and bioactives through the Therapeutics for Rare and Neglected Diseases (TRND) program and as part of the compound collection for the Tox21 initiative, a collaborative effort for toxicity screening among several government agencies including the US Environmental Protection Agency (EPA), the National Toxicology Program (NTP), the US Food and Drugs Administration (FDA), and the NCGC. Of the nearly 2750 small molecular entities (MEs) that have been approved for clinical use by US (FDA), EU (EMA), Japanese (NHI), and Canadian (HC) authorities and that are amenable to HTS screening, we currently possess 2,400 as part of our screening collection. The NPC resource currently consists of (i) the physical collection suitable for high throughput screening (HTS) and (ii) the informatics browser and database. Putting together the physical collection has been surprisingly challenging in terms of the time and effort required in the informatics, compound management and synthetic chemistry related activities required for this endeavor. We provide access to the NPC screening library through collaboration. Please contact our Scientific Director Dr. Chris Austin for additional information. The other half of the NPC resource is the NPC browser. This is a self-contained software that is actively developed and maintained by the informatics group to provide electronic access to the NPC content. The latest version of the NPC browser for various platforms can be downloaded.
Proper citation: NCGC Pharmaceutical Collection (RRID:SCR_006909) Copy
http://lincsportal.ccs.miami.edu/dcic-portal/
Portal which provides a unified interface for searching LINCS dataset packages and reagents. Users can use the portal to access datasets, small molecules, cells, genes, proteins and peptides, and antibodies.
Proper citation: LINCS Data Portal (RRID:SCR_014939) Copy
https://github.com/kstreet13/slingshot
Software R package for identifying and characterizing continuous developmental trajectories in single cell data. Cell lineage and pseudotime inference for single-cell transcriptomics.
Proper citation: Slingshot (RRID:SCR_017012) Copy
https://github.com/shendurelab/LACHESIS
Software tool for chromosome scale scaffolding of de novo genome assemblies based on chromatin interactions.Method exploits signal of genomic proximity in Hi-C datasets for ultra long range scaffolding of de novo genome assemblies.
Proper citation: LACHESIS (RRID:SCR_017644) Copy
Collection of data of protein sequence and functional information. Resource for protein sequence and annotation data. Consortium for preservation of the UniProt databases: UniProt Knowledgebase (UniProtKB), UniProt Reference Clusters (UniRef), and UniProt Archive (UniParc), UniProt Proteomes. Collaboration between European Bioinformatics Institute (EMBL-EBI), SIB Swiss Institute of Bioinformatics and Protein Information Resource. Swiss-Prot is a curated subset of UniProtKB.
Proper citation: UniProt (RRID:SCR_002380) Copy
One of the key challenges in the analysis of gene expression data is how to relate the expression level of individual genes to the underlying transcriptional programs and cellular state. The T-profiler tool hosted on this website uses the t-test to score changes in the average activity of pre-defined groups of genes. The gene groups are defined based on Gene Ontology categorization, ChIP-chip experiments, upstream matches to a consensus transcription factor binding motif, and location on the same chromosome, respectively. If desired, an iterative procedure can be used to select a single, optimal representative from sets of overlapping gene groups. A jack-knife procedure is used to make calculations more robust against outliers. T-profiler makes it possible to interpret microarray data in a way that is both intuitive and statistically rigorous, without the need to combine experiments or choose parameters. Currently, gene expression data from Saccharomyces cerevisiae and Candida albicans are supported. Users can submit their microarray data for analysis by clicking on one of the two organism-specific tabs above. Platform: Online tool
Proper citation: T-profiler (RRID:SCR_003452) Copy
http://avis.princeton.edu/pixie/index.php
bioPIXIE is a general system for discovery of biological networks through integration of diverse genome-wide functional data. This novel system for biological data integration and visualization, allows you to discover interaction networks and pathways in which your gene(s) (e.g. BNI1, YFL039C) of interest participate. The system is based on a Bayesian algorithm for identification of biological networks based on integrated diverse genomic data. To start using bioPIXIE, enter your genes of interest into the search box. You can use ORF names or aliases. If you enter multiple genes, they can be separated by commas or returns. Press ''submit''. bioPIXIE uses a probabilistic Bayesian algorithm to identify genes that are most likely to be in the same pathway/functional neighborhood as your genes of interest. It then displays biological network for the resulting genes as a graph. The nodes in the graph are genes (clicking on each node will bring up SGD page for that gene) and edges are interactions (clicking on each edge will show evidence used to predict this interaction). Most likely, the first results to load on the results page will be a list of significant Gene Ontology terms. This list is calculated for the genes in the biological network created by the bioPIXIE algorithm. If a gene ontology term appears on this list with a low p-value, it is statistically significantly overrepresented in this biological network. As you move the mouse over genes in the network, interactions involving these genes are highlighted. If you click on any of the highlighted interactions graph, evidence pop-up window will appear. The Evidence pop-up lists all evidence for this interaction, with links to the papers that produced this evidence - clicking these links will bring up the relevant source citation(s) in PubMed. You may need to download the Adobe Scalable Vector Graphic (SVG) plugin to utilize the visualization tool (you will be prompted if you need it).
Proper citation: bioPIXIE (RRID:SCR_004182) Copy
http://life.ccs.miami.edu/life/
LIFE search engine contains data generated from LINCS Pilot Phase, to integrate LINCS content leveraging semantic knowledge model and common LINCS metadata standards. LIFE makes LINCS content discoverable and includes aggregate results linked to Harvard Medical School and Broad Institute and other LINCS centers, who provide more information including experimental conditions and raw data. Please visit LINCS Data Portal.
Proper citation: LINCS Information Framework (RRID:SCR_003937) Copy
Software package that provides the ability to do a number of standard semantic similarity methods and includes novel methods for combining these with dynamic selection of anonymous grouping classes. Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible
Proper citation: OwlSim (RRID:SCR_006819) Copy
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