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DAPAR - Tools for the Differential Analysis of Proteins Abundance with R

The package DAPAR is a Bioconductor distributed R package which provides all the necessary functions to analyze quantitative data from label-free proteomics experiments. Contrarily to most other similar R packages, it is endowed with rich and user-friendly graphical interfaces, so that no programming skill is required (see `Prostar` package).

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proteomicsnormalizationpreprocessingmassspectrometryqualitycontrolgodataimportprostar1

6.36 score 2 stars 1 dependents 23 scripts 634 downloads

Prostar - Provides a GUI for DAPAR

This package provides a GUI interface for the DAPAR package. The package Prostar (Proteomics statistical analysis with R) is a Bioconductor distributed R package which provides all the necessary functions to analyze quantitative data from label-free proteomics experiments. Contrarily to most other similar R packages, it is endowed with rich and user-friendly graphical interfaces, so that no programming skill is required.

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proteomicsmassspectrometrynormalizationpreprocessingsoftwareguiprostar1

6.26 score 1 stars 11 scripts 489 downloads

DaparToolshed - Tools for the Differential Analysis of Proteins Abundance with R

The package DaparToolshed is a Bioconductor distributed R package which provides all the necessary functions to analyze quantitative data from label-free proteomics experiments. It is an update of our previous package DAPAR and contains more functions to analyze the data and uses MultAssayExperiment and SummarizedExperiment data structures. Contrarily to most other similar R packages, it is endowed with rich and user-friendly graphical interfaces, so that no programming skill is required (see `Prostar` package).

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proteomicsnormalizationpreprocessingmassspectrometryqualitycontroldataimportprostar2

5.68 score 2 stars 17 scripts 137 downloads

imputeLCMD - A Collection of Methods for Left-Censored Missing Data Imputation

A collection of functions for left-censored missing data imputation. Left-censoring is a special case of missing not at random (MNAR) mechanism that generates non-responses in proteomics experiments. The package also contains functions to artificially generate peptide/protein expression data (log-transformed) as random draws from a multivariate Gaussian distribution as well as a function to generate missing data (both randomly and non-randomly). For comparison reasons, the package also contains several wrapper functions for the imputation of non-responses that are missing at random. * New functionality has been added: a hybrid method that allows the imputation of missing values in a more complex scenario where the missing data are both MAR and MNAR.

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5.51 score 3 stars 8 dependents 211 scripts 2.6k downloads

omXplore - Vizualization tools for 'omics' datasets with R

This package contains a collection of functions (written as shiny modules) for the visualisation and the statistical analysis of omics data. These plots can be displayed individually or embedded in a global Shiny module. Additionaly, it is possible to integrate third party modules to the main interface of the package omXplore.

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softwareshinyappsmassspectrometrydatarepresentationguiqualitycontrolprostar2

5.10 score 25 scripts 271 downloads

DAPARdata - Data accompanying the DAPAR and Prostar packages

Mass-spectrometry based UPS proteomics data sets from Ramus C, Hovasse A, Marcellin M, Hesse AM, Mouton-Barbosa E, Bouyssie D, Vaca S, Carapito C, Chaoui K, Bruley C, Garin J, Cianferani S, Ferro M, Dorssaeler AV, Burlet-Schiltz O, Schaeffer C, Coute Y, Gonzalez de Peredo A. Spiked proteomic standard dataset for testing label-free quantitative software and statistical methods. Data Brief. 2015 Dec 17;6:286-94 and Giai Gianetto, Q., Combes, F., Ramus, C., Bruley, C., Coute, Y., Burger, T. (2016). Calibration plot for proteomics: A graphical tool to visually check the assumptions underlying FDR control in quantitative experiments. Proteomics, 16(1), 29-32.

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experimentdatamassspectrometrydataproteomeprostar1datapkg

4.86 score 2 dependents 10 scripts

DaparToolshedData - Data accompanying the DaparToolshed and Prostar 2 packages

Mass-spectrometry based UPS proteomics data sets from Ramus C, Hovasse A, Marcellin M, Hesse AM, Mouton-Barbosa E, Bouyssie D, Vaca S, Carapito C, Chaoui K, Bruley C, Garin J, Cianferani S, Ferro M, Dorssaeler AV, Burlet-Schiltz O, Schaeffer C, Coute Y, Gonzalez de Peredo A. Spiked proteomic standard dataset for testing label-free quantitative software and statistical methods. Data Brief. 2015 Dec 17;6:286-94 and Giai Gianetto, Q., Combes, F., Ramus, C., Bruley, C., Coute, Y., Burger, T. (2016). Calibration plot for proteomics: A graphical tool to visually check the assumptions underlying FDR control in quantitative experiments. Proteomics, 16(1), 29-32.

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experimentdataexperimenthubmassspectrometrydataprostar2datapkg

4.40 score 2 scripts