Search Results for "google-visualization-python"
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Showing 9 open source projects for "google-visualization-python"
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Corbata
CORe microBiome Analysis Tools
Corbata is a set of statistical tools that can be used to analyze the core microbiome across a set of samples. -
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DEAPathways
Differential Expression Analysis for Pathways
This project contains the source code associated with the PLoS Computational Biology publication: "Differential Expression Analysis for Pathways". The paper text can be found here: http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.1002967 -
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CoLabR
A simple user interface to the R software environment.
A simple user interface to the R software environment. It is designed for people new to R and provides the user with easy access to their variables and data along with pointers to the most basic commands. It also allows for multiple people to share data across different sessions on different machines. In this way it also offers a collaborative environment for people to work together in remote locations. -
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The igraph library
Library for creating and manipulating graphs
This is a library for creating and manipulating graphs with focus on speedy operations for large, sparse graphs. -
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imDEV
Tools for multivariate data visualization, exploration and analysis.
You may also like some newer work: http://createdatasol.com/ Project imDEV is an application of RExcel, which seamlessly integrates Excel and R for tasks focused on multivariate data visualization, exploration, and analysis. Interactive modules for dimensional reduction (imPCA), prediction (imPLS), feature selection, analysis of correlation (imCorrelations) and generation of networked structures (imGraph) provide an integrated environment for systems level analysis of multivariate data. -
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A Python library bringing together utilities I've written over the years for work in bioinformatics and biostatistics, which should be generally applicable outside these fields as well. Focuses on string processing, DBI, and math.
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Structlab is a machine learning C++ framework for structured domains, which provides a toolbox of learning methods and tools for preprocessing and visualization. It also provides a GUI to setup elaborate experiments in a visual and intuitive way.
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Quick reference for switching between mathematical computation environments for computer algebra, numeric processing and data visualisation. Examples are Matlab, IDL, SPlus, and their open-source counterparts Octave, Scilab, Python+NumPy and R.
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RGnome is a gtk based frontend for GNU R, which is a widely used language for statistical computing. It features a fully working R console and an editor with syntax highlighting.
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