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http://refgenie.databio.org

Software tool to organize, retrieve, and share genome analysis resources. Reference genome assembly asset manager. In addition to genome indexes, can manage any files related to reference genomes, including sequences and annotation files. Includes command line interface and server application that provides RESTful API, so it is useful for both tool development and analysis.

Proper citation: refgenie (RRID:SCR_017574) Copy   

•   Source: SciCrunch Registry

https://github.com/santeripuranen/SpydrPick

Software command line tool for performing direct coupling analysis of aligned categorical datasets. Used for analysis at scale of pan genomes of many bacteria. Incorporates correction for population structure, which adjusts for phylogenetic signal in data without requiring explicit phylogenetic tree.

Proper citation: SpydrPick (RRID:SCR_018176) Copy   

•   Source: SciCrunch Registry

https://github.com/santeripuranen/SuperDCA

Software tool for global direct coupling analysis of input genome alignments. Implements variant of pseudolikelihood maximization direct coupling analysis, with emphasis on optimizations that enable its use on genome scale. May be used to discover co evolving pairs of loci.Used for genome wide epistasis analysis.

Proper citation: SuperDCA (RRID:SCR_018175) Copy   

•   Source: SciCrunch Registry

https://bioconductor.org/packages/TCGAbiolinks/

Software R Bioconductor package for integrative analysis with TCGA data.TCGAbiolinks is able to access National Cancer Institute Genomic Data Commons thorough its GDC Application Programming Interface to search, download and prepare relevant data for analysis in R.

Proper citation: TCGAbiolinks (RRID:SCR_017683) Copy   

•   Source: SciCrunch Registry

https://crispy.secondarymetabolites.org

Web tool to design sgRNAs for CRISPR applications. Web tool based on CRISPy to design sgRNAs for any user-provided microbial genome. Implemented as standalone web application for Cas9 target prediction.

Proper citation: CRISPy-web (RRID:SCR_017970) Copy   

•   Source: SciCrunch Registry

https://github.com/slimsuite/pafscaff

Software as Pairwise mApping Format reference based Scaffold anchoring and super scaffolding tool. Dsigned for mapping genome assembly scaffolds to closely related chromosome level reference genome assembly.

Proper citation: PAFScaff (RRID:SCR_017976) Copy   

•   Source: SciCrunch Registry

https://metacpan.org/pod/Bio::CUA

Software tool as flexible and comprehensive codon usage analyzer. Used to analyze codon usage bias (CUB) and relevant problems.

Proper citation: Codon Usage Analyzer (RRID:SCR_018500) Copy   

•   Source: SciCrunch Registry

http://hgc.rockefeller.edu/

An interactive web server that enables researchers to prioritize any list of genes by their biological proximity to defined core genes (i.e. genes that are known to be associated with the phenotype), and to predict novel gene pathways.

Proper citation: Human Gene Connectome Server (RRID:SCR_002627) Copy   

•   Source: SciCrunch Registry

http://www.labspaces.net/DNA

Hi. I''m genegeek (aka Catherine Anderson). I realized during my PostDoc that I preferred learning and explaining new results to doing science so I started a non-traditional career of teaching and outreach. I''ll be using this space to explore public perception of genetics and other cool molecular biology stuff. I hope to add to the great discussions re: new science discoveries and general understanding of genetics. I''ve been running an outreach program and enjoy talking to non-experts about their opinions and understanding. I hope my enthusiasm for the topics can come through the screen. My posts are presented as opinion and commentary and do not represent the views of LabSpaces Productions, LLC, my employer, or my educational institution.

Proper citation: Daring Nucleic Adventures - genegeek (RRID:SCR_005215) Copy   

•   Source: SciCrunch Registry

http://gst.ornl.gov/

We are the Computational Biology and Bioinformatics Group of the Biosciences Division of Oak Ridge National Laboratory. We conduct genetics research and system development in genomic sequencing, computational genome analysis, and computational protein structure analysis. We provide bioinformatics and analytic services and resources to collaborators, predict prospective gene and protein models for analysis, provide user services for the general community, including computer-annotated genomes in Genome Channel. Our collaborators include the Joint Genome Institute, ORNL''s Computer Science and Mathematics Division, the Tennessee Mouse Genome Consortium, the Joint Institute for Biological Sciences, and ORNL''s Genome Science and Technology Graduate Program.

Proper citation: Computational Biology at ORNL (RRID:SCR_005710) Copy   

•   Source: SciCrunch Registry

http://www.compbio.dundee.ac.uk/gotcha/gotcha.php

GOtcha provides a prediction of a set of GO terms that can be associated with a given query sequence. Each term is scored independently and the scores calibrated against reference searches to give an accurate percentage likelihood of correctness. These results can be displayed graphically. Why is GOtcha different to what is already out there and why should you be using it? * GOtcha uses a method where it combines information from many search hits, up to and including E-values that are normally discarded. This gives much better sensitivity than other methods. * GOtcha provides a score for each individual term, not just the leaf term or branch. This allows the discrimination between confident assignments that one would find at a more general level and the more specific terms that one would have lower confidence in. * The scores GOtcha provides are calibrated to give a real estimate of correctness. This is expressed as a percentage, giving a result that non-experts are comfortable in interpreting. * GOtcha provides graphical output that gives an overview of the confidence in, or potential alternatives for, particular GO term assignments. The tool is currently web-based; contact David Martin for details of the standalone version. Platform: Online tool

Proper citation: GOtcha (RRID:SCR_005790) Copy   

•   Source: SciCrunch Registry

http://tabit.ucsd.edu/sdec/

A next-generation web-based application that aims to provide an integrated solution for both visualization and analysis of deep-sequencing data, along with simple access to public datasets.

Proper citation: Systems Transcriptional Activity Reconstruction (RRID:SCR_005622) Copy   

•   Source: SciCrunch Registry

http://plantgrn.noble.org/LegumeIP/

LegumeIP is an integrative database and bioinformatics platform for comparative genomics and transcriptomics to facilitate the study of gene function and genome evolution in legumes, and ultimately to generate molecular based breeding tools to improve quality of crop legumes. LegumeIP currently hosts large-scale genomics and transcriptomics data, including: * Genomic sequences of three model legumes, i.e. Medicago truncatula, Glycine max (soybean) and Lotus japonicus, including two reference plant species, Arabidopsis thaliana and Poplar trichocarpa, with the annotation based on UniProt TrEMBL, InterProScan, Gene Ontology and KEGG databases. LegumeIP covers a total 222,217 protein-coding gene sequences. * Large-scale gene expression data compiled from 104 array hybridizations from L. japonicas, 156 array hybridizations from M. truncatula gene atlas database, and 14 RNA-Seq-based gene expression profiles from G. max on different tissues including four common tissues: Nodule, Flower, Root and Leaf. * Systematic synteny analysis among M. truncatula, G. max, L. japonicus and A. thaliana. * Reconstruction of gene family and gene family-wide phylogenetic analysis across the five hosted species. LegumeIP features comprehensive search and visualization tools to enable the flexible query on gene annotation, gene family, synteny, relative abundance of gene expression.

Proper citation: LegumeIP (RRID:SCR_008906) Copy   

•   Source: SciCrunch Registry

http://hymenopteragenome.org/beebase/

Gene sequences and genomes of Bombus terrestris, Bombus impatiens, Apis mellifera and three of its pathogens, that are discoverable and analyzed via genome browsers, blast search, and apollo annotation tool. The genomes of two additional species, Apis dorsata and A. florea are currently under analysis and will soon be incorporated.BeeBase is an archive and will not be updated. The most up-to-date bee genome data is now available through the navigation bar on the HGD Home page.

Proper citation: BeeBase (RRID:SCR_008966) Copy   

•   Source: SciCrunch Registry

http://rgd.mcw.edu/rgdCuration/?module=portal&func=show&name=renal

An integrated resource for information on genes, QTLs and strains associated with a variety of kidney and renal system conditions such as Renal Hypertension, Polycystic Kidney Disease and Renal Insufficiency, as well as Kidney Neoplasms.

Proper citation: Renal Disease Portal (RRID:SCR_009030) Copy   

•   Source: SciCrunch Registry

http://www.cbil.upenn.edu/cgi-bin/tess/tess

TESS is a web tool for predicting transcription factor binding sites in DNA sequences. It can identify binding sites using site or consensus strings and positional weight matrices from the TRANSFAC, JASPAR, IMD, and our CBIL-GibbsMat database. You can use TESS to search a few of your own sequences or for user-defined CRMs genome-wide near genes throughout genomes of interest. Search for CRMs Genome-wide: TESS now has the ability to search whole genomes for user defined CRMs. Try a search in the AnGEL CRM Searches section of the navigation bar.. You can search for combinations of consensus site sequences and/or PWMs from TRANSFAC or JASPAR. Search DNA for Binding Sites: TESS also lets you search through your own sequence for TFBS. You can include your own site or consensus strings and/or weight matrices in the search. Use the Combined Search under ''Site Searches'' in the menu or use the box for a quick search. TESS assigns a TESS job number to all sequence search jobs. The job results are stored on our server for a period of time specified in the search submit form. During this time you may recall the search results using the form on this page. TESS can also email results to you as a tab-delimited file suitable for loading into a spreadsheet program. Query for Transcription Factor Info: TESS also has data browsing and querying capabilities to help you learn about the factors that were predicted to bind to your sequence. Use the Query TRANSFAC or Query Matrices links above or use the search interface provided from the home page.

Proper citation: TESS: Transcription Element Search System (RRID:SCR_010739) Copy   

•   Source: SciCrunch Registry

http://jjwanglab.org/snvrap

The web portal provides comprehensive local database of human genome variants with a user-friendly web page that provides a one-stop annotating and funtonal prediction service which is both convenient and up-to-date. A query can be accepted as either a dbSNP Id or a chromosomal location and our system will instantly provide all the annotation information in an interactive LD panel. The system can also simultaneously prioritize this variant based on additive effect mode by corresponding annotation information and evaluate the variant effect that is then displayed in a prioritization tree. Furthermore, cohort sequencing continuously produces lots of un-annotated variants such as rare variants or de novo variants, and our system can even fit this data by accepting genomic coordinates (hg19) to offer maximal annotations. Main Functions Over 40 up-to-date annotation items for human single nucleotide variations; Functional prediction for different types of variants; Dynamic LD panel for both HapMap and 1000 Genomes Project populations; Prioritization score and tree viewer based on variant functional model.

Proper citation: SNVrap (RRID:SCR_010512) Copy   

•   Source: SciCrunch Registry

http://www.jiffynet.org/

Web based instant protein network modeler for newly sequenced species. Web server designed to instantly construct genome scale protein networks using protein sequence data. Provides network visualization, analysis pages and solution for instant network modeling of newly sequenced species.

Proper citation: JiffyNet (RRID:SCR_011954) Copy   

•   Source: SciCrunch Registry

http://bio-bwa.sourceforge.net/

Software for aligning sequencing reads against large reference genome. Consists of three algorithms: BWA-backtrack, BWA-SW and BWA-MEM. First for sequence reads up to 100bp, and other two for longer sequences ranged from 70bp to 1Mbp.

Proper citation: BWA (RRID:SCR_010910) Copy   

•   Source: SciCrunch Registry

http://bejerano.stanford.edu/phenotree/

Web server to search for genes involved in given phenotypic difference between mammalian species. The mouse-referenced multiple alignment data files used to perform the forward genomics screen is also available. The webserver implements one strategy of a Forward Genomics approach aiming at matching phenotype to genotype. Forward genomics matches a given pattern of phenotypic differences between species to genomic differences using a genome-wide screen. In the implementation, the divergence of the coding region of genes in mammals is measured. Given an ancestral phenotypic trait that is lost in independent mammalian lineages, it is shown that searching for genes that are more diverged in all trait-loss species can discover genes that are involved in the given phenotype.

Proper citation: Phenotree (RRID:SCR_003591) Copy   

•   Source: SciCrunch Registry