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http://www.k-state.edu/

Public doctoral university located in Manhattan, Kansas that is involved with research, especially agricultural.

Proper citation: Kansas State University; Kansas; USA (RRID:SCR_001533) Copy   

•   Source: SciCrunch Registry

https://github.com/CollasLab/edd

A ChIP-seq peak caller for detection of megabase domains of enrichment.

Proper citation: Enriched Domain Detector (RRID:SCR_001693) Copy   

•   Source: SciCrunch Registry

https://www.clarku.edu/centers/geospatial-analytics/terrset-liberagis-features/idrisi-gis-analysis/

Geospatial software for monitoring and modeling the Earth system. Includes tools for GIS, image processing, surface analysis, vertical applications for land change analysis and earth trends exploration, and more.

Proper citation: IDRISI (RRID:SCR_001696) Copy   

•   Source: SciCrunch Registry

http://www.bioconductor.org/packages/devel/bioc/html/CNVrd2.html

A software package that uses next-generation sequencing data to measure human gene copy number for multiple samples, indentify SNPs tagging copy number variants and detect copy number polymorphic genomic regions.

Proper citation: CNVrd2 (RRID:SCR_001723) Copy   

•   Source: SciCrunch Registry

http://bioconductor.org/packages/2.13/bioc/html/sSeq.html

Software package to discover the genes that are differentially expressed between two conditions in RNA-seq experiments. Gene expression is measured in counts of transcripts and modeled with the Negative Binomial (NB) distribution using a shrinkage approach for dispersion estimation. The method of moment (MM) estimates for dispersion are shrunk towards an estimated target, which minimizes the average squared difference between the shrinkage estimates and the initial estimates. The exact per-gene probability under the NB model is calculated, and used to test the hypothesis that the expected expression of a gene in two conditions identically follow a NB distribution.

Proper citation: sSeq (RRID:SCR_001719) Copy   

•   Source: SciCrunch Registry

http://www.kcl.ac.uk/index.aspx

Public research university located in London, United Kingdom that offers undergraduate, graduate, and professional degree programs in medicine, economics, social sciences, etc.

Proper citation: King's College London; London; United Kingdom (RRID:SCR_001744) Copy   

•   Source: SciCrunch Registry

http://bioinformatics.med.yale.edu/group/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on April 10th,2023. An R code for Bayesian modeling of paired RNA-seq experiments.

Proper citation: pairedBayes (RRID:SCR_001738) Copy   

•   Source: SciCrunch Registry

http://sourceforge.net/projects/dnaclust/

Software program for clustering large number of short similar DNA sequences. It was originally designed for clustering targeted 16S rRNA pyrosequencing reads.

Proper citation: DNACLUST (RRID:SCR_001771) Copy   

•   Source: SciCrunch Registry

http://intermine.org/

An open source data warehouse system built for the integration and analysis of complex biological data that enables the creation of biological databases accessed by sophisticated web query tools. Parsers are provided for integrating data from many common biological data sources and formats, and there is a framework for adding data. InterMine includes a user-friendly web interface that works "out of the box" and can be easily customized for specific needs, as well as a powerful, scriptable web-service API to allow programmatic access to data.

Proper citation: InterMine (RRID:SCR_001772) Copy   

•   Source: SciCrunch Registry

http://www.atcc.org/

Global nonprofit biological resource center (BRC) and research organization that provides biological products, technical services and educational programs to private industry, government and academic organizations. Its mission is to acquire, authenticate, preserve, develop and distribute biological materials, information, technology, intellectual property and standards for the advancement and application of scientific knowledge. The primary purpose of ATCC is to use its resources and experience as a BRC to become the world leader in standard biological reference materials management, intellectual property resource management and translational research as applied to biomaterial development, standardization and certification. ATCC characterizes cell lines, bacteria, viruses, fungi and protozoa, as well as develops and evaluates assays and techniques for validating research resources and preserving and distributing biological materials to the public and private sector research communities.

Proper citation: ATCC (RRID:SCR_001672) Copy   

•   Source: SciCrunch Registry

http://www.bioconductor.org/packages/release/bioc/html/RSVSim.html

A software package for the simulation of deletions, insertions, inversions, tandem duplications and translocations of various sizes in any genome available as FASTA-file or data package in R. SV breakpoints can be placed uniformly accross the whole genome, with a bias towards repeat regions and regions of high homology (for hg19) or at user-supplied coordinates.

Proper citation: RSVSim (RRID:SCR_001777) Copy   

•   Source: SciCrunch Registry

http://www.annualreviews.org/

Annual Reviews offers comprehensive, timely collections of critical reviews written by leading scientists. It publishes authoritative, analytic reviews in 37 focused disciplines within the Biomedical, Life, Physical, and Social Sciences. The mission of Annual Reviews is to provide systematic, periodic examinations of scholarly advances in a number of fields of science through critical authoritative reviews. The comprehensive critical review not only summarizes a topic but also roots out errors of fact or concept and provokes discussion that will lead to new research activity. The critical review is an essential part of the scientific method. Sponsors: Annual Reviews is a non-profit organization created and managed by scientists to serve science by publishing reviews in 40 different scientific fields.

Proper citation: Annual Reviews: A Nonprofit Scientific Publisher (RRID:SCR_001655) Copy   

•   Source: SciCrunch Registry

http://www.bioconductor.org/packages/release/bioc/html/TCC.html

An R package that provides a series of functions for differential expression analysis from RNA-seq count data using robust normalization strategy (called DEGES). The basic idea of DEGES is that potential differentially expressed genes or transcripts (DEGs) among compared samples should be removed before data normalization to obtain a well-ranked gene list where true DEGs are top-ranked and non-DEGs are bottom ranked. This can be done by performing a multi-step normalization strategy (called DEGES for DEG elimination strategy). A major characteristic of TCC is to provide the robust normalization methods for several kinds of count data (two-group with or without replicates, multi-group/multi-factor, and so on) by virtue of the use of combinations of functions in other sophisticated packages (especially edgeR, DESeq, and baySeq).

Proper citation: TCC (RRID:SCR_001779) Copy   

•   Source: SciCrunch Registry

http://cmb.gis.a-star.edu.sg/ChIPSeq/paperCCAT.htm

THIS RESOURCE IS OUT OF SERVICE, documented on April 5, 2017, A software package for the analysis of ChIP-seq data with negative control., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: CCAT (RRID:SCR_001843) Copy   

•   Source: SciCrunch Registry

http://blog.expressionplot.com/

Software package consisting of a default back end, which prepares raw sequencing or Affymetrix microarray data, and a web-based front end, which offers a biologically centered interface to browse, visualize, and compare different data sets.

Proper citation: ExpressionPlot (RRID:SCR_001904) Copy   

•   Source: SciCrunch Registry

https://urgi.versailles.inra.fr/Tools/S-Mart

Software toolbox that manages your RNA-Seq and ChIP-Seq data and also produces many different plots to visualize your data. It performs several tasks that are usually required during the analysis of mapped RNA-Seq and ChIP-Seq reads, including data selection and data visualization. It includes the selection (or the exclusion) of the data that overlaps with a reference set, clustering and comparative analysis. It also provides many ways to visualize data: size of the reads, density on the genome, distance with respect to a reference set, and the correlation of two data sets (with cloud plots). A computer science background is not required to run it through a graphical interface and it can be run on any personal computer, yielding results within an hour for most queries.

Proper citation: S-MART (RRID:SCR_001908) Copy   

•   Source: SciCrunch Registry

http://www.kaist.edu/html/en/index.html

Institute dedicated to research in science and technology in South Korea modeled after a research university.

Proper citation: Korea Advanced Institute of Science and Technology; Daejeon; South Korea (RRID:SCR_001902) Copy   

•   Source: SciCrunch Registry

https://github.com/raphael-group/THetA

An algorithm that estimates the tumor purity and clonal / subclonal copy number aberrations directly from high-throughput DNA sequencing data.

Proper citation: THetA (RRID:SCR_001860) Copy   

•   Source: SciCrunch Registry

http://www.ualberta.ca/

Public research university in Edmonton, Alberta, Canada that offers degree programs in a variety of fields including business, arts, education, engineering, nursing, and medicine.

Proper citation: University of Alberta; Alberta; Canada (RRID:SCR_001853) Copy   

•   Source: SciCrunch Registry

http://www.bioconductor.org/packages/release/bioc/html/SamSPECTRAL.html

Software that identifies cell population in flow cytometry data. It demonstrates significant advantages in proper identification of populations with non-elliptical shapes, low density populations close to dense ones, minor subpopulations of a major population and rare populations. It samples large data such that spectral clustering is possible while preserving density information in edge weights. More specifically, given a matrix of coordinates as input, SamSPECTRAL first builds the communities to sample the data points. Then, it builds a graph and after weighting the edges by conductance computation, the graph is passed to a classic spectral clustering algorithm to find the spectral clusters. The last stage of SamSPECTRAL is to combine the spectral clusters. The resulting connected components estimate biological cell populations in the data sample.

Proper citation: SamSPECTRAL (RRID:SCR_001858) Copy   

•   Source: SciCrunch Registry