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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.
https://cran.r-project.org/web/packages/ggplot2/index.html
Open source software package for statistical programming language R to create plots based on grammar of graphics. Used for data visualization to break up graphs into semantic components such as scales and layers.
Proper citation: ggplot2 (RRID:SCR_014601) Copy
http://cran.r-project.org/web/packages/muma/
Software that provides guidelines for the whole process of metabolomic data interpretation, from data pre-processing, to dataset exploration and visualization, to identification of potentially interesting metabolites. Guidelines outline the following processes: preprocessing of high-throughput data (normalization and scalings); principal component analysis with help tool for choosing best-separating principal components and automatic testing for outliers; automatic univariate analysis for parametric and non-parametric data, with generation of specific reports (volcano and box plots); partial least square discriminant analysis (PLS-DA); orthogonal partial least square discriminant analysis (OPLS-DA); Statistical Total Correlation Spectroscopy (STOCSY); and Ratio Analysis Nuclear Magnetic Resonance (NMR) Spectroscopy (RANSY).
Proper citation: MUMA (RRID:SCR_002412) Copy
https://CRAN.R-project.org/package=tidyverse
Software tool as collection of R packages designed for data science which share underlying design philosophy, grammar, and data structures. Packages work in harmony because they share common data representations and API design. Used in everyday data analyses.
Proper citation: tidyverse (RRID:SCR_019186) Copy
https://CRAN.R-project.org/package=MASS
Software R package to support functions and datasets for Venables and Ripley MASS. Used for statistical and graphical analysis of data.
Proper citation: Modern Applied Statistics with S (RRID:SCR_019125) Copy
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Welcome to the Neuroscience Information Framework Project, designed to serve the biomedical research community. NIF maintains the largest searchable collection of neuroscience data, the largest catalog of biomedical resources, and the largest ontology for neuroscience on the web. We welcome all feedback and suggestions and are actively looking for resource providers to make their resources accessible through NIF. Learn about the tools available to help you share your data and discover a dynamic inventory of Web-based neuroscience resources.
