Open Source S/R Bio-Informatics Software for Linux
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S/R Bio-Informatics Software for Linux
View 14 business solutionsBrowse free open source S/R Bio-Informatics Software for Linux and projects below. Use the toggles on the left to filter open source S/R Bio-Informatics Software for Linux by OS, license, language, programming language, and project status.
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coronavirus
The coronavirus dataset
The coronavirus package gives a tidy format dataset of the 2019 Novel Coronavirus COVID-19 (2019-nCoV) epidemic. Relevant and updated information about the virus, such as summary of new cases by country and total number of cases by region can be retrieved from this package. The raw data is pulled and arranged by the Johns Hopkins University Center for Systems Science and Engineering, which is gathered from various leading sources including the World Health Organization, China CDC, US CDC, European Centre for Disease Prevention and Control, and Australia Government Department of Health. -
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SPINA
Structure parameter inference approach for endocrine feedback control
SPINA is software for the rapid, reliable and accurate determination of constant structure parameters of endocrine feedback control systems. It is a class of static function tests that require nothing more than steady-state concentrations of hormones or metabolites obtained in vivo. The first version of this cybernetic approach had been developed for the evaluation of the functional status of the thyroid gland, i.e. thyroid's secretory capacity (gain of thyroid, GT or SPINA-GT) and sum activity of peripheral deiodinases (GD or SPINA-GD). A second version has been established for insulin-glucose homeostasis. It delivers the secretory capacity of pancreatic beta cells (SPINA-GBeta), an estimate for the insulin receptor amplification (SPINA-GR) and a static disposition index as a measure for the loop gain of the feedback loop (SPINA-DI). Both implementations of SPINA have been validated in more than 50 clinical studies based on large cohorts. -
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We are developing data standards and software tools that implement these standards to develop a systemic approach to modeling, capturing, analyzing and disseminating flow cytometry data.
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EigenMS is a normalization method implemented in R (and older version in Matlab) available as a set of two functions that should be used in a sequence. Please download EigenMS.zip file (latest version). Latest version uploaded in October 2017 has a bugfix for single treatment group normalization. Rescaling has been omitted from 2015. EigenMS utilizes SVD to detect bias trends in the data and eliminates them. EigenMS eliminates effects from known and unknown factors and can be utilized for any -omic platform. We have shown its utility in LC-MS/MS and metabolomics in the following two papers: 1) PMID: 19602524. "Normalization of peak intensities in bottom-up MS-based proteomics using singular value decomposition". Karpievitch YV, Taverner T, Adkins JN, Callister SJ, Anderson GA, Smith RD, Dabney AR. Bioinformatics 2009 2) "Metabolomics data normalization with EigenMS" Karpievitch YV, Nikolic SB, Wilson R, Sharman JE, Edwards LM. PLoS One 2014
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CyberUnits
Class library for computational cybernetics
CyberUnits is a cross-platform class library for rapid development of high-performance computer simulations in life sciences. It supports modelling for biomedical cybernetics and systems biology with Object Pascal. -
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An implementation of the Kernel-based Orthogonal Projections to Latent Structures (K-OPLS) method for MATLAB and R. The supplied functionality includes e.g. cross-validation, kernel parameter optimization, model diagnostics and plot tools.
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estimate_project
ESTIMATE
ESTIMATE (Estimation of STromal and Immune cells in MAlignant Tumors using Expression data) is a new approach to use gene expression signature to infer the fraction of stromal and immune cells in tumor tissues. -
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We developed a systematic algorithmic solution for quantitative drug sensitivity scoring (DSS), based on continuous modeling and integration of multiple dose-response relationships in high-throughput compound testing studies. License: The DSS R-package is made available under the terms of the GNU General Public License, which means that the source code is freely available for use within other software, but if you alter the code and distribute it, you must make the new source code freely available as well. This software is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY. In case you use the package in your work, we do appreciate a citation to a DSS publication. Citation: Yadav et al. (2014), Quantitative scoring of differential drug sensitivity for individually optimized anticancer therapies. Scientific Reports 4, 5193; DOI:10.1038/srep05193 Please visit the link below for details
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Collection of tools for performing robust case-control disease and quantitative trait association studies using Copy Number Variants- Latest version should now be downloaded from Bioconductor
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MoPAC
The Modular Pipeline for the Analysis of CRISPR screens
To facilitate the comparison of gene essentialities in two or more cell samples, we propose MoPAC (Modular Pipeline for Analysis of CRISPR screens), a Shiny-driven interactive tool for differential essentiality analysis in CRISPR/Cas9 screens. For installation and usage instructions please refer to the wiki page. -
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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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ANDES. This is a library and a set of applications that can be used to analyze the results of deep sequencing results. (See Li et al.: ANDES: Statistical tools for the ANalyses of DEep Sequencing. BMC Research Notes 2010 3:199.)
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AWclust is easy to use non-parametric population structure analysis software written for R with a GUI interface. Just point and click and you will be on your way to discovering the important cluster information in your SNP data sets.
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BEMoDA
Dissolution profile comparison Model Dependent-Independent Approach
Dissolution profile comparison (Biowaiver aid) Model Dependent-Independent Approach scripts for in-vitro dissolution profile comparison as proposed by Sathe et al. in 1996 (Sathe PM, Tsong Y, Shah VP. In-vitro dissolution profile comparison: statistics and analysis, model dependent approach. Pharm Res. 1996 Dec;13(12):1799-803) and Tsong et al. in 1996 (Tsong Y, Hammerstrom T, Sathe P, Shah VP. (1996) Statistical Assessment of Mean Differences between Two Dissolution Data Sets, Drug Info. J. 30:1105-1112). -
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BayesRate
Bayesian estimation of diversification rates
BayesRate is a program to estimate speciation and extinction rates from dated phylogenies in a Bayesian framework. The methods are described in: Silvestro, D., Schnitzler, J. and Zizka, G. (2011) A Bayesian framework to estimate diversification rates and their variation through time and space. BMC Evolutionary Biology, 11, 311 Silvestro D., Zizka G. & Schulte K. (2014) Disentangling the effects of key innovations on the diversification of Bromelioideae (Bromeliaceae). Evolution, 68, 163-175. -
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BD-Func
Bidirectional Functional Enrichment of Gene Expression Data
BD-Func is an algorithm to predict activation or inhibition of pathways based upon gene expression patterns. If you use BD-Func, please cite: Warden C, Kanaya N, Chen S, and Yuan Y-C. (2013) BD-Func: A Streamlined Algorithm for Predicting Activation and Inhibition of Pathways. peerJ, 1:e159 -
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COHCAP
City of Hope CpG Island Analysis Pipeline
COHCAP (City of Hope CpG Island Analysis Pipeline, pronounced "co-cap") is an algorithm to analyze single-nucleotide resolution methylation data (Illumina 450k methylation array, targeted BS-Seq, etc.). Please note: 1) The SourceForge version of COHCAP is no longer being updated. Please see the GitHub version: https://github.com/cwarden45/COHCAP This was the source repository for the Bioconductor version, with some changes after the decision to only provide the code through GitHub. 2) In addition to the original NAR paper, please see the following links: Benchmarks: http://www.nature.com/protocolexchange/protocols/2965#/introduction Protocol Exchange Files: http://sourceforge.net/projects/cohcap/files/Protocol_Exchange_Example.zip 3) Custom Annotation Files (including EPIC Array): https://sourceforge.net/projects/cohcap/files/additional_Bioconductor_annotations.zip/download -
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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.
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IAP.G2P
IAP - the Integrated Analysis Pipeline
The Integrated Analysis Platform (IAP) has been designed and developed to support the analysis of large-scale image data sets of different camera systems. It aims in bridging different data domains and in integrating different approaches to data analysis and post-processing. -
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MCPerm: Monte Carlo SNP permutation
Monte Carlo permutation method for SNP multiple test correlation
MCPerm: A Monte Carlo permutation method for multiple test correlation in case-control association study Traditional permutation (TradPerm) test is an important non-parametric analysis method which can be treated as the gold standard for multiple testing corrections in case-control association study. However, it relies on the original single nucleotide polymorphism (SNP) genotypes and phenotypes data to perform a large number of random shuffles, and thus it is computationally intensive, especially for genome-wide association study (GWAS). To improve the calculation speed without changing the size of the TradPerm p-value, we developed a Monte Carlo permutation (MCPerm) method as an efficient alternative to TradPerm. Methods: MCPerm does not need to shuffle the original genotypes and phenotypes data. It uses Monte Carlo method, employs two-step hypergeometric distribution to generate the random number of genotypes (AA, Aa and aa) in cases and controls. -
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Mass-Up
MALDI-TOF data analysis tool
Mass-Up is an Open-Source mass spectrometry utility for proteomics designed to support the preprocessing and analysis of MALDI-TOF mass spectrometry data. Mass-Up includes several tools and operations to load, preprocess and analyze MALDI-TOF data. -
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Multiple optima
Scripts used to detect multiple optima of likelihood on real data.
R scripts and sequence data used in the paper "Multiple local maxima for likelihoods of phylogenetic trees constructed from biological data." by McComish BJ, Schliep KP and Penny D (submitted to Systematic Biology). -
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The Protein Similarity Network
Human protein similarity network used to predict drug safety.
This is the protein similarity network - PSIN. Here, the nodes are human proteins and they are linked only if they share considerable sequence similarity. We found that this network is particularly useful to distinguish approved from problematic drug-targets. Here you also find the complete set of programs and datasets we used for this purpose. Free to help further test and develop this project. Your help and expertise are much appreciated ! If you have any questions, please do not hesitate to contact us in the forum or by email. Please see the original manuscript: Lopes, TJS, et al. (2015) - "Identifying problematic drugs based on the characteristics of their targets" - Frontiers in Pharmacology doi: 10.3389/fphar.2015.00186 -
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dataMAPPs
R based pipeline for MHC-associated peptide proteomics (MAPPs) data
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 -
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ADTEx
Aberration detection in tumour exome
Aberration Detection in Tumour Exome (ADTEx) is a tool for copy number variation (CNV) detection for whole-exome data from paired tumour/matched normal samples.
