MCL-edge is an integrated command-line driven workbench for large scale network analysis. It includes programs for the computation of shortest paths, diameter, clustering coefficient, betweenness centrality, and network shuffles. A module for loading and analyzing gene expression data as a network is provided. The MCL algorithm is a fast and highly scalable cluster algorithm for networks based on stochastic flow. The flow process employed by the algorithm is mathematically sound and intrinsically tied to cluster structure, which is revealed as the imprint left by the process. The threaded implementation has handled networks with millions of nodes within hours and is widely used in the fields of bioinformatics, graph clustering, and network analysis.
QtIPy is a simple GUI-based automator for IPython notebooks. It allows you to attach triggers to files, folders, or timers to automatically run notebooks. IPython notebooks are great for interactively working through analysis problems, so why would you want to automatically run them? To get a record of how you ran your analysis! By running a notebook through QtIPy you get the output, figures, and a step by step log of how the analysis was performed all in the same folder.
Wandora is a general purpose data extraction, management, and publishing application based on Topic Maps and Java. Wandora has a graphical user interface, layered presentation of knowledge, several data storage options, rich data extraction, import and export capabilities, and an embedded HTTP server that enables dynamic publication of Topic Maps. Wandora is well suited for rapid ontology construction and knowledge mashups.
Pathomx is a workflow-based tool for the analysis of metabolomic and other omics datasets. It is interactive, visual, extensible, intelligent, and free for any use. It lets you dynamically build analysis workflows using the interactive editor. Drag and drop connections between plugin tools to create a complete workflow through which to run your analysis. Data can be loaded and processed automatically, and new approaches tested simply by connecting tools.
Wunderbar is a program which is able to identify mislabeled samples in genotype data when a few extra independent genotypes are available ("genetic barcoding"). Wunderbar calculates the likelihood that genotype mismatches have occurred by chance. It is capable of reliable and sensitive detection of sample mismatches and swaps even in the presence of numerous genotyping errors and in the presence of linkage disequibrilium between the individual genotypes. It only requires a few SNPs to work well.
LabKey Server is open source software that helps scientists manage, analyze, and share complex datasets. It supports tandem mass spectrometry, flow cytometry, assays for neutralizing antibodies, Luminex, observational studies, and secure, Web-based collaboration. The software is modular, configurable, and customizable. It can be installed in your institution on any modern hardware and operating system. It is designed to integrate with your existing systems, instruments, and work flows, and to be readily adapted by skilled programmers to novel methods of inquiry. The project is under active development by a team of professional software engineers and a community of active contributors. New versions are released about four times per year.
SHOGUN is a machine learning toolbox whose focus is on large scale kernel methods and especially on Support Vector Machines (SVM). It provides a generic SVM object interfacing to several different SVM implementations, all making use of the same underlying, efficient kernel implementations. Apart from SVMs and regression, SHOGUN also features a number of linear methods like Linear Discriminant Analysis (LDA), Linear Programming Machine (LPM), (Kernel) Perceptrons, and algorithms to train hidden Markov models. SHOGUN can be used from within C++, Matlab, R, Octave, and Python.