Open Source Data Analytics Tools - Page 13
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Pyclamp
A Python package used to extract and analyse electrophysiological data
Pyclamp is Python package used to extract and analyse electrophysiological data. A graphical user interface has been developed to allow a user to run the pack- age without requiring any knowledge of Python code. Presently, Pyclamp is designed to perform very specific forms of analysis on evoked synaptic responses: Data analysis (under development) : This is a highly user-interactive en-vironment that can be used to discriminate synaptic events, obtain various measures of their kinetics and size, and output the results. Quantal analysis : This part of the package performs simple variance-mean analysis and Bayesian quantal analysis to estimate the quantal sizea dn number of release sites among other measures. -
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Pyphant is a framework for scientific data analysis. It features a flexible plugin architecture allowing for the application in many different fields. For the analysis a graph of processing steps is constructed, that can be applied via the cli as well.
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Python Laboratory Operations Toolkit
many useful snippets for using python in a laboratory
A toolkit of Python software useful in a laboratory data acquisition and analysis environment. Includes support for such protocols as VXI-11 (and its extension, LXI), Vernier LabPro (now very old), and National Instruments DSTP (now very old). Also includes data analysis and modelling tidbits. Python3 updates are on the way in the very near future for the biggest packages. the vxi11 package is fully up-to-date, although see the blog post about python 3.13 -
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PythonStatsLab
A collection of useful statistical functions written in Python
There are functions for numerical integration of the standard normal probability distribution. They can be used to find probabilities, find z-alpha values, calculate confidence interval, etc. New functionality I wish to add are hypothesis testing and calculation of p-value, type I & II errors, etc. These functions would come in handy to anyone taking introductory or intermediate-level courses in probability, statistics and data analysis. There are several numerical integration techniques (Riemann sum, Simpson's method, Taylor expansion, etc.) that can be employed in this task, which I hope to add soon. Projected Future Improvements: -Estimation with 2 means -Student's t-distribution -Hart's algorithm for integrating CDF -
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QME-DEV Workbench (wxScipy) is a data analysis workbench based on Python, SciPy, Numpy and MatPlotLib(PyLab) and uses wxPython for the GUI. It can be used for non-linear analysis with a large set of experimental or generated data. Load/Acquire / Save/ Gr
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QSAS plug-ins
Plug-ins for the space physics data analysis software QSAS.
The project is concerned with developing new plug-ins for the space plasma analysis software QSAS. The plug-ins are developed mainly for the Cluster II mission, Champ and Swarm. QSAS can be downloaded from: http://www.sp.ph.ic.ac.uk/csc-web/QSAS/ -
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QSoas
Command-driven data analysis program
QSoas is a generic y=f(x) data processing program. -
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Query2Report
Simple open source business intelligence and reporting solution
Query2Report provides a simple opensource business intelligence platform that allows users to build report/dashboard for business analytics or enterprise reporting. The application transforms bunch SQL queries to beautiful google charts. The application caters to real time reporting with automatic refresh functionality. Refer to video tutorials Concepts - https://youtu.be/NdEUZ2suiv8 Data Analytics Demo - https://youtu.be/evCf74Ou7kg Data Forecast Demo - https://youtu.be/Nmi1UIDpFpM Report Showcase - https://youtu.be/gxlEGq5iSm8 Getting Started - https://youtu.be/vyU7BUE5rbs Building First Report - https://youtu.be/MZm6rhf2_Ts Source Repo GitHub : https://github.com/yogeshsd/query2report -
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QuickNGS
Next-Generation Sequencing workflow system
QuickNGS is a software for efficient and highly reproducible data analysis for Next-Generation Sequencing. -
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QuickNXS
Polarized ToF reflectivity raw data analysis tool
Data evaluation tool for the magnetism reflectometer at the spallation neutron source (BL-4A@SNS). Reads raw nexus files (HDF5) of histogrammed or event mode data to create reflectivity curves and 2D Q-maps. -
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QuickRNASeq
A pipeline for large scale RNA-seq data analysis
We have implemented QuickRNASeq, an open-source based pipeline for large scale RNA-seq data analysis. QuickRNASeq takes advantage of parallel computing resources, a careful selection of previously published algorithms for RNA-seq read mapping, counting and quality control, and a three-stage strategy to build a fully automated workflow. We also implemented built-in functionalities to detect sample swapping or mislabeling in large-scale RNA-seq studies. Our pipeline significantly lifts large-scale RNA-seq data analysis to the next level of automation and visualization. Please take a look at our test run project report and get a taste of its rich interactive visualization features. http://baohongz.github.io/QuickRNASeq QuickRNASeq user guide can be downloaded or is accessible online as well http://baohongz.github.io/QuickRNASeq/guide.html For more on QuickRNASeq, please see our paper http://bmcgenomics.biomedcentral.com/articles/10.1186/s12864-015-2356-9 Enjoy QuickRNASeq -
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QuiclickRNAseq
An integrated pipeline for RNA-seq analysis
Quiclick is a python framework for RNA-seq data analysis, including data trimming, mapping, counting and RNA editing analysis. -
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R Hadoop for Big Data
Download Free Associated R open source script files for big data analy
Download Free Associated R open source script files for big data analysis with Hadoop and R These are R script source file from Ram Venkat from a past Meetup we did at http://www.meetup.com/R-Matlab-Users/events/85160532/ Also, there is a long video and Powerpoint presentation slide PDF with R files at: http://quantlabs.net/blog/2012/11/how-to-use-hadoop-and-r-for-big-data-parallel-processing-free-download-pdf/ Download source files from http://quantlabs.net/blog/2012/11/download-free-associated-r-open-source-script-files-for-big-data-analysis-with-hadoop-and-r-rstats-hadoop/ -
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A collection of code, bundled into a single R package, to perform several aspects of data management, image pre-processing, data analysis and statistical inference related to the quantitative analysis of dynamic contrast-enhanced MRI (DCE-MRI).
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RATH
Automated Data Analysis Software, Open Source Augmented Analytic BI
RATH is beyond an open-source alternative to Data Analysis and Visualization tools such as Tableau. It automates your Exploratory Data Analysis workflow with an Augmented Analytic engine by discovering patterns, insights, causals and presents those insights with powerful auto-generated multi-dimensional data visualization. -
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RCFPD
Random Collection of Functions for Proteomics Data Analysis
An R package for distribution of data analysis functionality used by the Proteomics Core at Weill Cornell Medical College in Qatar. -
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ROOTSNNS is a set of C++ classes which allows one to use the Stuttgart Neural Network Simulator kernel (ansi-C) within the ROOT, a data analysis package. Multiple ANNs can be built, trained, and tested, while results and ANN performance can be saved.
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ROOTlib
C++ lib, that provides access to multiple ROOT routines (root.cern.ch)
This C++ lib is used and created to provide easy methods based on ROOT (a CERN data analysis framework). It was developed for use in practical courses but is not limited to. In addition it is ported step by step into Python. -
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RSS Atom Feed Analytics With MapReduce
This is a data analytics project for RSS feeds using hadoop MapReduce
This project accepts the output of jatomrss project as the input. It applies the MR logic on the same to perform the analytics -
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RStatServer is a system for quickly developing and deploying web applications that integrate statistical computations and graphics. It is built using the Zope web application develeopment system and the open-source statistical data analysis environment R
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RUCKUS-DATA-STUDIO
RUCKUS Analytics - Data Studio Dashboard Repository
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RadiationHelper
Alpha, Beta, Gamma measurements and Nuclide exposure
RadiationHelper is a data analysis tool for : 1. gross alpha and beta radiation measurement and detector calibration using experimental data (counts acquired by alpha-beta devices). 2. gamma spectroscopy measurements and detector calibration using experimental data (spectra acquired by acquisition software such as Assayer, Gamma Vision, Maestro) 3. gross alpha,beta, gamma detector efficiencies and gamma peak efficiency can be theoretical computed using Monte-Carlo simulation technique for radiation transport (based on EGSnrc toolkit) 4.dose assessment in human body exposed to radiations from nuclides in several common scenarios such as air exposure, water submersion, ground surface, internal ingestion or inhalation. 5. quick dosimetry and shielding computations. It is platform independent (written entirely in Java). Source code included in jar files! Also, available on GitHub: https://github.com/ZiliasTheSaint/RadiationHelper.git Checkout for dependent modules! -
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Random Bits Regression
Random Bits Regression is a strong general predictor.
We proposed an accurate, robust and fast general predictor (RBR) for regression and classification in big data era. The application of this method is very broad, from science to industry, finance and health. The accuracy and robustness improvement of our method over existing method could bring huge benefits in some critical applications. For example, natural disaster prediction, stock price prediction, personal/population disease prediction. The fast-speed nature of our method not only allows big data analysis but also enables real-time recognition and predictions. The RBR framework also hints the mechanism of brain function and leads to a "wide learning" hypothesis. We believe that this method will make a great impact and enable many downstream applications. -
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Reproducible-research
A Reproducible Data Analysis Workflow with R Markdown, Git, Make, etc.
In this tutorial, we describe a workflow to ensure long-term reproducibility of R-based data analyses. The workflow leverages established tools and practices from software engineering. It combines the benefits of various open-source software tools including R Markdown, Git, Make, and Docker, whose interplay ensures seamless integration of version management, dynamic report generation conforming to various journal styles, and full cross-platform and long-term computational reproducibility. The workflow ensures meeting the primary goals that 1) the reporting of statistical results is consistent with the actual statistical results (dynamic report generation), 2) the analysis exactly reproduces at a later point in time even if the computing platform or software is changed (computational reproducibility), and 3) changes at any time (during development and post-publication) are tracked, tagged, and documented while earlier versions of both data and code remain accessible. -
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While resting-state fMRI is drawing more and more attention, there has not been a software for its data analysis. Based on MATLAB, we developed a package named REST. Currently REST has three main functions: function connectivity, ReHo and ALFF.