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https://github.com/big-data-lab-team/spot

Open source software tool for file based localization of numerical perturbations in data analysis pipelines. Identifies components in pipeline, at resolution level of system process, that produce different results in different execution conditions.

Proper citation: Spot (RRID:SCR_018915) Copy   

•   Source: SciCrunch Registry

https://cran.r-project.org/web/packages/GALLO/vignettes/GALLO.html

Software R package developed for accurate annotation of genes and quantitative trait loci located in regions identified in common genomic analyses performed in livestock, such as Genome Wide Association Studies and transcriptomics using RNA-Sequencing. Allows graphical visualization of gene and QTL annotation results, data comparison among different grouping factors like methods, breeds, tissues, statistical models, studies and QTL enrichment in different livestock species including cattle, pigs, sheep, and chickens.

Proper citation: Genomic Annotation in Livestock for positional candidate LOci (RRID:SCR_019212) Copy   

•   Source: SciCrunch Registry

https://github.com/SMI/SmiServices

Software suite of tools for cataloguing and anonymising DICOM files, as used for Scottish Medical Imaging project. Software suite of microservices for loading, anonymising, linking and extracting large volumnes of dicom medical images to support medical research. Platform allows dicom tags extracted from clinical images to be loaded into MongoDB and relational database tables for purposes of generating anonymous linked research extracts including image anonymisation.

Proper citation: SMI Services (RRID:SCR_018881) Copy   

•   Source: SciCrunch Registry

https://cran.r-project.org/package=psych

Software R package for multivariate analysis and scale construction using factor analysis, principal component analysis, cluster analysis and reliability analysis.Procedures for Psychological, Psychometric, and Personality Research. Used for personality, psychometric theory and experimental psychology.

Proper citation: psych (RRID:SCR_021744) Copy   

•   Source: SciCrunch Registry

https://github.com/AdmiralenOla/Scoary

Software tool that scores components of pan genome for associations to observed phenotypic traits while accounting for population stratification, with minimal assumptions about evolutionary processes.Designed to take gene presence absence.csv file from Roary as well as traits file created by user and calculate associations between all genes in accessory genome and traits. It reports list of genes sorted by strength of association per trait.

Proper citation: Scoary (RRID:SCR_021087) Copy   

•   Source: SciCrunch Registry

http://fantom.gsc.riken.jp/4/

The FANTOM consortium is an international collaborative research project initiated and organized by the RIKEN Omics Science Center. In earlier FANTOM efforts we cloned and annotated 103,000 full-length cDNAs from mouse and distributed them to researchers throughout the world. FANTOM1-3 focused on identifying the transcribed components of mammalian cells. This work improved estimates of the total number of genes and their alternative transcript isoforms in both human and mouse, expanded gene families, and revealed that a large fraction of the transcriptome is non-coding. In addition, with the development of Cap Analysis of Gene Expression (CAGE) FANTOM3 could map a large fraction of transcription start sites and revise our models of promoter structure. This updated web resource provides the previous FANTOM results mapped to current genome builds and presents the results of FANTOM4. In FANTOM4 the focus has changed to understanding how these components work together in the context of a biological network. Using deepCAGE (deep sequencing with CAGE) we monitored the dynamics of transcription start site (TSS) usage during a time course of monocytic differentiation in the acute myeloid leukemia cell line THP-1. This allowed us to identify active promoters, monitor their relative expression and define relevant regions for carrying out transcription factor binding site predictions. Computational methods were then used to build a network model of gene expression in this leukemia and the transcription factors key to its regulation. This work gives the first picture of the wiring between genes involved in acute myeloid leukemia and provides a strategy for identifying key factors that determine cell fates. In addition to the network, FANTOM4 data was used in two additional analyses. The first identified a novel class of short RNAs associated with transcription start sites and the second focused on the role of repetitive element expression in the transcriptome. TOOLS *Genome Browser: graphical display of genomic features, such as promoters, exon structures, H3K9 acetylation, transcription factors positioning on the genome, coupled with gene and promoter activities. *EdgeExpressDB: regulatory interactions, such as transcriptional regulation, post-transcriptional silencing with miRNA, and PPI, coupled with gene and promoter activities. *SwissRegulon: FANTOM4 TF regulation is predicted using Motif Activity Response Analysis (MARA) developed by Erik van Nimwegen at Biozentrum. Follow the link to carry out MARA on your own dataset. *Custom Tracks on the UCSC Genome Browser: FANTOM4 tracks on the UCSC Genome Browser Database. *The RIKEN integrated database of mammals: Integration of FANTOM4 data with other mammalian resources, in particular, produced by RIKEN.

Proper citation: FANTOM DB (RRID:SCR_002678) Copy   

•   Source: SciCrunch Registry

http://www.omicsexpress.com/sva.php

Software package to annotate, visualize, and analyze the genetic variants identified through next-generation sequencing studies, including whole-genome sequencing (WGS) and exome sequencing studies. SVA aims to provide the research community with a user-friendly and efficient tool to analyze large amount of genetic variants, and to facilitate the identification of the genetic causes of human diseases and related traits.

Proper citation: SVA (RRID:SCR_002155) Copy   

•   Source: SciCrunch Registry

https://github.com/eduardporta/e-Driver

Software tool to identify cancer driver genes based on linear annotations of biological regions such as protein domains.Uses information on three-dimensional structures of mutated proteins to identify specific structural features. Then algorithm analyzes whether these features are enriched in cancer somatic mutations and are candidate driver genes.

Proper citation: e-Driver (RRID:SCR_002674) Copy   

•   Source: SciCrunch Registry

http://www.ncbi.nlm.nih.gov/igblast/

THIS RESOURCE IS NO LONGER IN SERVICE.Documented on January 4,2023. IgBLAST was developed at NCBI to facilitate analysis of immunoglobulin V region sequences in GenBank. In addition to performing a regular BLAST search, IgBLAST has several additional functions: - Reports the germline V, D and J gene matches to the query sequence. - Annotates the immunoglobulin domains (FWR1 through FWR3). - Matches the returned hits (for databases other than germline genes) to the closest germline V genes, making it easier to identify related sequences. - Reveals the V(D)J junction details such as nucleotide homology between the ends of V(D)J segments and N nucleotide insertions. D and J gene reporting is only for nucleotide sequence search and requires a stretch of five or more nucleotide identity between the query and D or J genes. Sponsors: This resource is supported by the National Center for Biotechnology Information, a division of the U.S. National Library of Medicine.

Proper citation: IgBLAST (RRID:SCR_002873) Copy   

•   Source: SciCrunch Registry

http://systemsbio.ucsd.edu/GoSurfer/

GoSurfer uses Gene Ontology (GO) information to analyze gene sets obtained from genome-wide computations or microarray analyses. GoSurfer is a graphical interactive data mining tool. It associates user input genes with GO terms and visualizes such GO terms as a hierarchical tree. Users can manipulate the tree output by various means, like setting heuristic thresholds or using statistical tests. Significantly important GO terms resulted from a statistical test can be highlighted. All related information are exportable either as texts or as graphics. Platform: Windows compatible

Proper citation: GoSurfer (RRID:SCR_005789) Copy   

•   Source: SciCrunch Registry

http://www.bioinfo.no/tools/bomp

BOMP is a tool for prediction of beta-barrel integral outer membrane proteins. The user may submit a list of proteins, and receive a list of predicted BOMPs. The program, called the beta-barrel Outer Membrane protein Predictor (BOMP), is based on two separate components to recognize integral beta-barrel proteins. The first component is a C-terminal pattern typical of many integral beta-barrel proteins. The second component calculates an integral beta-barrel score of the sequence based on the extent to which the sequence contains stretches of amino acids typical of transmembrane -strands. To use the BOMP tool simply paste your fasta-formatted sequences into the text area, or choose a file which contains sequences. Then hit the submit button. It is possible to perform a BLAST search parallel with the predictions, which may be suitable in some cases. Using the BLAST search will however increase the running time substantially. Sponsors: This work was supported in part by grants from the Norwegian Research Council [SUP 140785/420 (GABI); FUGE/CBU151899/ISO], and the Meltzer Foundation, University of Bergen. Keywords: Beta-barrel, Membrane, Protein, Program, Software, Beta strand, Bacteria,

Proper citation: BOMP: beta-barrel Outer Membrane protein Predictor (RRID:SCR_007268) Copy   

•   Source: SciCrunch Registry

http://www.psychopy.org

Open source application to allow the presentation of stimuli and collection of data for a wide range of neuroscience, psychology and psychophysics experiments. It is intended as a free, powerful alternative to Presentation or e-Prime.

Proper citation: PsychoPy (RRID:SCR_006571) Copy   

•   Source: SciCrunch Registry

https://varscan.sourceforge.net/

Platform-independent, technology-independent software tool for identifying SNPs and indels in massively parallel sequencing of individual and pooled samples. Given data for a single sample, VarScan identifies and filters germline variants based on read counts, base quality, and allele frequency. Given data for a tumor-normal pair, VarScan also determines the somatic status of each variant (Germline, Somatic, or LOH) by comparing read counts between samples. (entry from Genetic Analysis Software).

Proper citation: VarScan (RRID:SCR_006849) Copy   

•   Source: SciCrunch Registry

http://zfishbook.org/

Collection of revertible protein trap gene-breaking transposon (GBT) insertional mutants in zebrafish with active or cryopreserved lines from initially identified lines. Open to community-wide contributions including expression and functional annotation and represents world-wide central hub for information on how to obtain these lines from diverse members of International Zebrafish Protein Trap Consortium (IZPTC) and integration within other zebrafish community databases including Zebrafish Information Network (ZFIN), Ensembl and National Center for Biotechnology Information. Registration allows users to save their favorite lines for easy access, request lines from Mayo Clinic catalog, contribute to line annotation with appropriate credit, and puts them on optional mailing list for future zfishbook newletters and updates.

Proper citation: zfishbook (RRID:SCR_006896) Copy   

•   Source: SciCrunch Registry

http://sourceforge.net/projects/htqc/

A software toolkit including statistics tool for illumina high-throughput sequencing data, and filtration tools for sequence quality, length, tail quality, etc..

Proper citation: HTQC (RRID:SCR_006448) Copy   

•   Source: SciCrunch Registry

http://droog.gs.washington.edu/ldSelect.html

Software program that analyzes patterns of linkage disequilibrium (LD) between polymorphic sites in a locus, and bins the SNPs on the basis of a threshold level of LD as measured by r2. (entry from Genetic Analysis Software), THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: LDSELECT (RRID:SCR_007010) Copy   

•   Source: SciCrunch Registry

http://watson.hgen.pitt.edu/register/soft_doc.html

Software application that is a faster version of SLINK (entry from Genetic Analysis Software)

Proper citation: FASTSLINK (RRID:SCR_008664) Copy   

•   Source: SciCrunch Registry

http://mga.bionet.nsc.ru/soft/pedpeel/

Software program that prepares pedigree data for calculation of Elston-Stewarts'' likelihood function. It finds an optimal way to peel a pedigree and returns text file containing 7 description arrays (entry from Genetic Analysis Software)

Proper citation: PEDPEEL (RRID:SCR_008436) Copy   

•   Source: SciCrunch Registry

http://www.homepages.ed.ac.uk/pmckeigu/admixmap/index.html

General-purpose program for modelling admixture, using marker genotypes and trait data on a sample of individuals from an admixed population (such as African-Americans), where the markers have been chosen to have extreme differentials in allele frequencies between two or more of the ancestral populations between which admixture has occurred. The main difference between ADMIXMAP and classical programs for estimation of admixture such as ADMIX is that ADMIXMAP is based on a multilevel model for the distribution of individual admixture in the population and the stochastic variation of ancestry on hybrid chromosomes. This makes it possible to model the associations of ancestry between linked marker loci, and the association of a trait with individual admixture or with ancestry at a linked marker locus. (entry from Genetic Analysis Software)

Proper citation: ADMIXMAP (RRID:SCR_009035) Copy   

•   Source: SciCrunch Registry

http://mga.bionet.nsc.ru/soft/index.html

Software application that allows drawing pedigrees with a difficult structure, those containing consanguinity loops, and those individuals with multiple mates or several related families (entry from Genetic Analysis Software)

Proper citation: PEDIGREEQUERY (RRID:SCR_009041) Copy   

•   Source: SciCrunch Registry