Open Source S/R Bio-Informatics Software - Page 2

dataMAPPs allows routine and efficient processing of data from immunogenicity studies applying the MAPPs peptidomics technology to detect potential MHCI- or MHC-II epitopes as presented by dendritic cells (DC). It features quality control of the raw data, across-sample/across-donor normalization and visualization of results in a heatmap style (heatMAPPs). dataMAPPs' core is a generic R library that can be tailored to specific projects via dedicated control scripts which also allow reproducible recalculation of results. Consult README file for installation and usage instructions. Further documentation is supplied in PDF format. dataMAPPs is published under GPL license by a team of scientists working for Hoffmann-La Roche AG in Basel, Switzerland. The software is provided as is, to hopefully benefit other researchers. Related Publication in the Journal of Proteome Research: DOI: 10.1021/acs.jproteome.0c00309

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.

ALEXA-Seq is a method for using massively parallel paired-end transcriptome sequencing for 'alternative expression analysis'.

AUTOMATED GENOTYPE CALLING OF LUMINEX ASSAYS

Acanthocephalan Proboscis Profiler is a tool for detecting acanthocephalan morphotypes.

Tools to build molecular-docking activity prediction models by PLS regression with iterative training and pose-selection. Descriptors include (i) docking score(s), (ii) pharmacophore features, (iii) multi-feature descriptors learned by decision trees.

A collection of bioinformatics-related software created by members of Cancer Research UK (possibly among others).

BigBang/Horizon is a proteomics data analysis pipeline with focus on the shotgun LC/MSMS workflow.

Metagenomics yields enormous numbers of microbial sequences that can be assigned a metabolic function. Using such data to infer community-level metabolic divergence is hindered by the lack of a suitable statistical framework. Here, we describe a novel hierarchical Bayesian model, called BiomeNet (Bayesian inference of metabolic networks), for inferring differential prevalence of metabolic networks among microbial communities. To infer the structure of community-level metabolic interactions, BiomeNet applies a mixed-membership modelling framework to enzyme abundance information. The basic idea is that the mixture components of the model (metabolic reactions, subnetworks, and networks) are shared across all groups (microbiome samples), but the mixture proportions vary from group to group. Through this framework, the model can capture nested structures within the data. BiomeNet is unique in modeling each metagenome sample as a mixture of complex metabolic systems (metabosystems).

A population-based method for DNA copy number analysis: recurrent copy number aberration indentification in multiple samples (with no need of single-sample calling). Developed for a quick analysis of high resolution and large population data.

CNV Workshop is a web-enabled platform for analyzing genome variation such as copy number variation (CNV). Learn about CNV Workshop in our associated BMC Bioinformatics manuscript: http://www.biomedcentral.com/1471-2105/11/74

Copy Number Analysis for Targeted Resequencing (CONTRA) is a tool for copy number variation (CNV) detection for targeted resequencing data such as those from whole-exome capture data.

The Canopy project is an initiative to merge and expand the functionality of Perl-speaks-NONMEM (PsN), Census, Xpose and PopED. The goal is to produce a coherent, inclusive and convenient platform for pharmacometric data analysis.

Toolchain for quantification of fluorescence intensity and morphological parameters in single cells using microscope based cytometry.

Celsius is a data warehouse that provides web services for upload, archival, download, annotation, quantification, and normalization of all Affymetrix microarray platforms.

Chipster is a biologist-friendly analysis software for high-throughput data. It contains over 200 analysis tools for next generation sequencing (NGS), microarray and proteomics data. Users can combine tools in automatic analysis workflows, which can be shared. Chipster's interactive visualizations allow users to select datapoints and create new gene lists. For NGS data Chipster contains a built-in genome browser, which highlights SNPs and automatically indexes BAM files and calculates coverage. Chipster’s ability to provide a biologist-friendly access to a powerful analysis platform is technically based on a desktop application user interface, a flexible distributed architecture, and the ability to integrate many types of analysis tools (command line, R/Bioconductor, Java, Web Services etc). The platform is generic and easily extendable to other areas, even beyond bioinformatics. For more information, please see http://chipster.csc.fi and http://genomebiology.com/1471-2164/12/

ClinStudyWeb is designed to provide a flexible infrastructure for managing patient and assay data from clinical studies. It uses a plugin system for study-specific web forms and arbitrarily complex test classifiers, and supports XML import/export.

- MixtureModel_v1r1: overlapping community algorithm [3], which includes novel partition density and fuzzy modularity metrics. - OpenMP versions of algorithms in [1] are available to download. - Main suite containing three community detection algorithms based on the Modularity measure containing: Geodesic and Random Walk edge Betweenness [1] and Spectral Modularity [2]. Collaborator: Theologos Kotsos. [1] M. Newman & M. Girvan, Physical Review, E 69 (026113), 2004. [2] M. Newman, Physical Review E, 74(3):036104, 2006. [3] B. Ball et al, An efficient and principled method for detecting communities in networks, 2011. The suite is based upon the fast community algorithm implemented by Aaron Clauset <aaron@cs.unm.edu>, Chris Moore, Mark Newman, and the R IGraph library Copyright (C) 2007 Gabor Csardi <csardi@rmki.kfki.hu>. It also makes of the classes available from Numerical Recipies 3rd Edition W. Press, S. Teukolsky, W. Vetterling, B. Flanne

Corbata is a set of statistical tools that can be used to analyze the core microbiome across a set of samples.

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

Living cells are complex, dynamic, self-regulatory, interactive systems, showing differential states across time and space. Complexity of cellular systems is highlighted with the multi-layered regulatory mechanisms involving the interactions between bio-molecules (such as DNA, RNA, mi-RNA and proteins). These interactions are analyzed in the form of static networks. Likewise, number of experimental techniques like microarray, RNASeq allows quantification of cellular dynamics and aid in discerning differential gene expression across diverse conditions. Computational biology is in need of methods for integration of static networks and gene expression data, since it provides interesting insights into the dynamics of biological systems. DEN is an R/Bioconductor based package designed to assemble different types of human bio-molecular interactions as a complete interactome and contains functions to extract dynamic active networks by integration of gene expression data.

Use statistical methods to analyze time-course data (gene expression microarray and RNA-seq data in particular, but not limited to). Apply significance tests to filter out only significant genes or time series. Cluster time series into similar groups. Generate network models, including linear or non-linear models. Variable selection and optimization routines included. Written in Scala and R. The application is a cross-platform desktop app with a simple GUI and is fully functional currently. The app was and is developed at the University of Rochester (http://cbim.urmc.rochester.edu) under the GPL 3.0 license. This is a fork of that project.

DetectiV is an R package for the analysis of pathogen detection microarrays

DEW is a platform that allows users to explore RNA-Seq data. A web-based Graphical User Interface is included. The analysis proceeds as such: gapped alignments are performed and corrected for length, PCR and fragment bias so that a Fragment Per (effective) Kilobase per Million of reads (FPKM) is estimated as well as the simpler Reads Per Kb per Million of reads (RPKM). When provided with multiple isoforms and in the ‘contextual’ mode, corrections include a expectation maximization algorithm estimates effective expression profiles and a corrected alignment is produced. For each gene the user provides, DEW computes coverage descriptive statistics (RPKM, FKMP and total, mean and median corrected counts), expression profiles (normalized as R/FPKM and trimmed mean of fold change). DEW allows users to explore the data by providing interactive graphs.