Showing 51 of total 51 results (show query)
bioc
xcms:LC-MS and GC-MS Data Analysis
Framework for processing and visualization of chromatographically separated and single-spectra mass spectral data. Imports from AIA/ANDI NetCDF, mzXML, mzData and mzML files. Preprocesses data for high-throughput, untargeted analyte profiling.
Maintained by Steffen Neumann. Last updated 19 days ago.
immunooncologymassspectrometrymetabolomicsbioconductorfeature-detectionmass-spectrometrypeak-detectioncpp
196 stars 14.31 score 984 scripts 11 dependentsbioc
MSnbase:Base Functions and Classes for Mass Spectrometry and Proteomics
MSnbase provides infrastructure for manipulation, processing and visualisation of mass spectrometry and proteomics data, ranging from raw to quantitative and annotated data.
Maintained by Laurent Gatto. Last updated 19 days ago.
immunooncologyinfrastructureproteomicsmassspectrometryqualitycontroldataimportbioconductorbioinformaticsmass-spectrometryproteomics-datavisualisationcpp
131 stars 12.76 score 772 scripts 36 dependentsbioc
pRoloc:A unifying bioinformatics framework for spatial proteomics
The pRoloc package implements machine learning and visualisation methods for the analysis and interogation of quantitiative mass spectrometry data to reliably infer protein sub-cellular localisation.
Maintained by Lisa Breckels. Last updated 6 days ago.
immunooncologyproteomicsmassspectrometryclassificationclusteringqualitycontrolbioconductorproteomics-dataspatial-proteomicsvisualisationopenblascpp
15 stars 10.31 score 101 scripts 2 dependentsbioc
CAMERA:Collection of annotation related methods for mass spectrometry data
Annotation of peaklists generated by xcms, rule based annotation of isotopes and adducts, isotope validation, EIC correlation based tagging of unknown adducts and fragments
Maintained by Steffen Neumann. Last updated 5 months ago.
immunooncologymassspectrometrymetabolomics
11 stars 10.27 score 175 scripts 6 dependentsbioc
IPO:Automated Optimization of XCMS Data Processing parameters
The outcome of XCMS data processing strongly depends on the parameter settings. IPO (`Isotopologue Parameter Optimization`) is a parameter optimization tool that is applicable for different kinds of samples and liquid chromatography coupled to high resolution mass spectrometry devices, fast and free of labeling steps. IPO uses natural, stable 13C isotopes to calculate a peak picking score. Retention time correction is optimized by minimizing the relative retention time differences within features and grouping parameters are optimized by maximizing the number of features showing exactly one peak from each injection of a pooled sample. The different parameter settings are achieved by design of experiment. The resulting scores are evaluated using response surface models.
Maintained by Thomas Lieb. Last updated 5 months ago.
immunooncologymetabolomicsmassspectrometry
34 stars 8.14 score 41 scriptsbioc
metaMS:MS-based metabolomics annotation pipeline
MS-based metabolomics data processing and compound annotation pipeline.
Maintained by Yann Guitton. Last updated 5 months ago.
immunooncologymassspectrometrymetabolomics
15 stars 7.50 score 15 scriptsbioc
NormalyzerDE:Evaluation of normalization methods and calculation of differential expression analysis statistics
NormalyzerDE provides screening of normalization methods for LC-MS based expression data. It calculates a range of normalized matrices using both existing approaches and a novel time-segmented approach, calculates performance measures and generates an evaluation report. Furthermore, it provides an easy utility for Limma- or ANOVA- based differential expression analysis.
Maintained by Jakob Willforss. Last updated 5 months ago.
normalizationmultiplecomparisonvisualizationbayesianproteomicsmetabolomicsdifferentialexpressionbioconductorbioinformaticslimma
22 stars 7.30 score 38 scripts 1 dependentsbioc
DEP:Differential Enrichment analysis of Proteomics data
This package provides an integrated analysis workflow for robust and reproducible analysis of mass spectrometry proteomics data for differential protein expression or differential enrichment. It requires tabular input (e.g. txt files) as generated by quantitative analysis softwares of raw mass spectrometry data, such as MaxQuant or IsobarQuant. Functions are provided for data preparation, filtering, variance normalization and imputation of missing values, as well as statistical testing of differentially enriched / expressed proteins. It also includes tools to check intermediate steps in the workflow, such as normalization and missing values imputation. Finally, visualization tools are provided to explore the results, including heatmap, volcano plot and barplot representations. For scientists with limited experience in R, the package also contains wrapper functions that entail the complete analysis workflow and generate a report. Even easier to use are the interactive Shiny apps that are provided by the package.
Maintained by Arne Smits. Last updated 5 months ago.
immunooncologyproteomicsmassspectrometrydifferentialexpressiondatarepresentation
7.10 score 628 scriptsbioc
cliqueMS:Annotation of Isotopes, Adducts and Fragmentation Adducts for in-Source LC/MS Metabolomics Data
Annotates data from liquid chromatography coupled to mass spectrometry (LC/MS) metabolomics experiments. Based on a network algorithm (O.Senan, A. Aguilar- Mogas, M. Navarro, O. Yanes, R.Guimerà and M. Sales-Pardo, Bioinformatics, 35(20), 2019), 'CliqueMS' builds a weighted similarity network where nodes are features and edges are weighted according to the similarity of this features. Then it searches for the most plausible division of the similarity network into cliques (fully connected components). Finally it annotates metabolites within each clique, obtaining for each annotated metabolite the neutral mass and their features, corresponding to isotopes, ionization adducts and fragmentation adducts of that metabolite.
Maintained by Oriol Senan Campos. Last updated 5 months ago.
metabolomicsmassspectrometrynetworknetworkinferencecpp
12 stars 6.91 score 25 scriptsbioc
pRolocGUI:Interactive visualisation of spatial proteomics data
The package pRolocGUI comprises functions to interactively visualise spatial proteomics data on the basis of pRoloc, pRolocdata and shiny.
Maintained by Lisa Breckels. Last updated 5 months ago.
8 stars 6.90 score 3 scriptsbioc
peakPantheR:Peak Picking and Annotation of High Resolution Experiments
An automated pipeline for the detection, integration and reporting of predefined features across a large number of mass spectrometry data files. It enables the real time annotation of multiple compounds in a single file, or the parallel annotation of multiple compounds in multiple files. A graphical user interface as well as command line functions will assist in assessing the quality of annotation and update fitting parameters until a satisfactory result is obtained.
Maintained by Arnaud Wolfer. Last updated 5 months ago.
massspectrometrymetabolomicspeakdetectionfeature-detectionmass-spectrometry
12 stars 6.65 score 23 scriptsbioc
LOBSTAHS:Lipid and Oxylipin Biomarker Screening through Adduct Hierarchy Sequences
LOBSTAHS is a multifunction package for screening, annotation, and putative identification of mass spectral features in large, HPLC-MS lipid datasets. In silico data for a wide range of lipids, oxidized lipids, and oxylipins can be generated from user-supplied structural criteria with a database generation function. LOBSTAHS then applies these databases to assign putative compound identities to features in any high-mass accuracy dataset that has been processed using xcms and CAMERA. Users can then apply a series of orthogonal screening criteria based on adduct ion formation patterns, chromatographic retention time, and other properties, to evaluate and assign confidence scores to this list of preliminary assignments. During the screening routine, LOBSTAHS rejects assignments that do not meet the specified criteria, identifies potential isomers and isobars, and assigns a variety of annotation codes to assist the user in evaluating the accuracy of each assignment.
Maintained by Henry Holm. Last updated 5 months ago.
immunooncologymassspectrometrymetabolomicslipidomicsdataimportadductalgaebioconductorhplc-esi-mslipidmass-spectrometryoxidative-stress-biomarkersoxidized-lipidsoxylipinsplankton
8 stars 6.56 score 9 scriptsbioc
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.
Maintained by Samuel Wieczorek. Last updated 5 months ago.
proteomicsmassspectrometrynormalizationpreprocessingsoftwareguiprostar1
1 stars 6.48 score 15 scriptsbioc
PrInCE:Predicting Interactomes from Co-Elution
PrInCE (Predicting Interactomes from Co-Elution) uses a naive Bayes classifier trained on dataset-derived features to recover protein-protein interactions from co-elution chromatogram profiles. This package contains the R implementation of PrInCE.
Maintained by Michael Skinnider. Last updated 5 months ago.
proteomicssystemsbiologynetworkinference
8 stars 6.38 score 25 scripts
rickhelmus
patRoon:Workflows for Mass-Spectrometry Based Non-Target Analysis
Provides an easy-to-use interface to a mass spectrometry based non-target analysis workflow. Various (open-source) tools are combined which provide algorithms for extraction and grouping of features, extraction of MS and MS/MS data, automatic formula and compound annotation and grouping related features to components. In addition, various tools are provided for e.g. data preparation and cleanup, plotting results and automatic reporting.
Maintained by Rick Helmus. Last updated 12 days ago.
mass-spectrometrynon-targetcppopenjdk
65 stars 6.24 score 43 scriptsbioc
metaseqR2:An R package for the analysis and result reporting of RNA-Seq data by combining multiple statistical algorithms
Provides an interface to several normalization and statistical testing packages for RNA-Seq gene expression data. Additionally, it creates several diagnostic plots, performs meta-analysis by combinining the results of several statistical tests and reports the results in an interactive way.
Maintained by Panagiotis Moulos. Last updated 21 days ago.
softwaregeneexpressiondifferentialexpressionworkflowsteppreprocessingqualitycontrolnormalizationreportwritingrnaseqtranscriptionsequencingtranscriptomicsbayesianclusteringcellbiologybiomedicalinformaticsfunctionalgenomicssystemsbiologyimmunooncologyalternativesplicingdifferentialsplicingmultiplecomparisontimecoursedataimportatacseqepigeneticsregressionproprietaryplatformsgenesetenrichmentbatcheffectchipseq
7 stars 6.05 score 3 scriptsbioc
CluMSID:Clustering of MS2 Spectra for Metabolite Identification
CluMSID is a tool that aids the identification of features in untargeted LC-MS/MS analysis by the use of MS2 spectra similarity and unsupervised statistical methods. It offers functions for a complete and customisable workflow from raw data to visualisations and is interfaceable with the xmcs family of preprocessing packages.
Maintained by Tobias Depke. Last updated 5 months ago.
metabolomicspreprocessingclustering
10 stars 6.04 score 22 scriptsbioc
RMassBank:Workflow to process tandem MS files and build MassBank records
Workflow to process tandem MS files and build MassBank records. Functions include automated extraction of tandem MS spectra, formula assignment to tandem MS fragments, recalibration of tandem MS spectra with assigned fragments, spectrum cleanup, automated retrieval of compound information from Internet databases, and export to MassBank records.
Maintained by RMassBank at Eawag. Last updated 5 months ago.
immunooncologybioinformaticsmassspectrometrymetabolomicssoftwareopenjdk
6.02 score 26 scriptsbioc
arrayQualityMetrics:Quality metrics report for microarray data sets
This package generates microarray quality metrics reports for data in Bioconductor microarray data containers (ExpressionSet, NChannelSet, AffyBatch). One and two color array platforms are supported.
Maintained by Mike Smith. Last updated 5 months ago.
microarrayqualitycontrolonechanneltwochannelreportwriting
1 stars 5.98 score 193 scriptsbioc
autonomics:Unified Statistical Modeling of Omics Data
This package unifies access to Statistal Modeling of Omics Data. Across linear modeling engines (lm, lme, lmer, limma, and wilcoxon). Across coding systems (treatment, difference, deviation, etc). Across model formulae (with/without intercept, random effect, interaction or nesting). Across omics platforms (microarray, rnaseq, msproteomics, affinity proteomics, metabolomics). Across projection methods (pca, pls, sma, lda, spls, opls). Across clustering methods (hclust, pam, cmeans). It provides a fast enrichment analysis implementation. And an intuitive contrastogram visualisation to summarize contrast effects in complex designs.
Maintained by Aditya Bhagwat. Last updated 2 months ago.
softwaredataimportpreprocessingdimensionreductionprincipalcomponentregressiondifferentialexpressiongenesetenrichmenttranscriptomicstranscriptiongeneexpressionrnaseqmicroarrayproteomicsmetabolomicsmassspectrometry
5.89 score 5 scripts
adafede
cascade:Contextualizing untargeted Annotation with Semi-quantitative Charged Aerosol Detection for pertinent characterization of natural Extracts
This package provides the infrastructure to perform Automated Composition Assessment of Natural Extracts.
Maintained by Adriano Rutz. Last updated 5 days ago.
metabolite annotationcharged aerosol detectorsemi-quantitativenatural productscomputational metabolomicsspecialized metabolome
2 stars 5.76 score 40 scripts 1 dependentsbioc
pvca:Principal Variance Component Analysis (PVCA)
This package contains the function to assess the batch sourcs by fitting all "sources" as random effects including two-way interaction terms in the Mixed Model(depends on lme4 package) to selected principal components, which were obtained from the original data correlation matrix. This package accompanies the book "Batch Effects and Noise in Microarray Experiements, chapter 12.
Maintained by Jianying LI. Last updated 5 months ago.
5.67 score 111 scripts 1 dependentsbioc
bandle:An R package for the Bayesian analysis of differential subcellular localisation experiments
The Bandle package enables the analysis and visualisation of differential localisation experiments using mass-spectrometry data. Experimental methods supported include dynamic LOPIT-DC, hyperLOPIT, Dynamic Organellar Maps, Dynamic PCP. It provides Bioconductor infrastructure to analyse these data.
Maintained by Oliver M. Crook. Last updated 2 months ago.
bayesianclassificationclusteringimmunooncologyqualitycontroldataimportproteomicsmassspectrometryopenblascppopenmp
4 stars 5.56 score 3 scriptsbioc
tilingArray:Transcript mapping with high-density oligonucleotide tiling arrays
The package provides functionality that can be useful for the analysis of high-density tiling microarray data (such as from Affymetrix genechips) for measuring transcript abundance and architecture. The main functionalities of the package are: 1. the class 'segmentation' for representing partitionings of a linear series of data; 2. the function 'segment' for fitting piecewise constant models using a dynamic programming algorithm that is both fast and exact; 3. the function 'confint' for calculating confidence intervals using the strucchange package; 4. the function 'plotAlongChrom' for generating pretty plots; 5. the function 'normalizeByReference' for probe-sequence dependent response adjustment from a (set of) reference hybridizations.
Maintained by Zhenyu Xu. Last updated 5 months ago.
microarrayonechannelpreprocessingvisualization
5.48 score 5 scripts 1 dependentsbioc
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).
Maintained by Samuel Wieczorek. Last updated 5 months ago.
proteomicsnormalizationpreprocessingmassspectrometryqualitycontrolgodataimportprostar1
2 stars 5.42 score 22 scripts 1 dependentsbioc
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.
Maintained by Samuel Wieczorek. Last updated 4 days ago.
softwareshinyappsmassspectrometrydatarepresentationguiqualitycontrolprostar2
5.32 score 23 scriptsbioc
ptairMS:Pre-processing PTR-TOF-MS Data
This package implements a suite of methods to preprocess data from PTR-TOF-MS instruments (HDF5 format) and generates the 'sample by features' table of peak intensities in addition to the sample and feature metadata (as a singl<e ExpressionSet object for subsequent statistical analysis). This package also permit usefull tools for cohorts management as analyzing data progressively, visualization tools and quality control. The steps include calibration, expiration detection, peak detection and quantification, feature alignment, missing value imputation and feature annotation. Applications to exhaled air and cell culture in headspace are described in the vignettes and examples. This package was used for data analysis of Gassin Delyle study on adults undergoing invasive mechanical ventilation in the intensive care unit due to severe COVID-19 or non-COVID-19 acute respiratory distress syndrome (ARDS), and permit to identfy four potentiel biomarquers of the infection.
Maintained by camille Roquencourt. Last updated 5 months ago.
softwaremassspectrometrypreprocessingmetabolomicspeakdetectionalignmentcpp
7 stars 5.15 score 3 scriptsbioc
squallms:Speedy quality assurance via lasso labeling for LC-MS data
squallms is a Bioconductor R package that implements a "semi-labeled" approach to untargeted mass spectrometry data. It pulls in raw data from mass-spec files to calculate several metrics that are then used to label MS features in bulk as high or low quality. These metrics of peak quality are then passed to a simple logistic model that produces a fully-labeled dataset suitable for downstream analysis.
Maintained by William Kumler. Last updated 5 months ago.
massspectrometrymetabolomicsproteomicslipidomicsshinyappsclassificationclusteringfeatureextractionprincipalcomponentregressionpreprocessingqualitycontrolvisualization
3 stars 5.13 score 5 scriptsbioc
topdownr:Investigation of Fragmentation Conditions in Top-Down Proteomics
The topdownr package allows automatic and systemic investigation of fragment conditions. It creates Thermo Orbitrap Fusion Lumos method files to test hundreds of fragmentation conditions. Additionally it provides functions to analyse and process the generated MS data and determine the best conditions to maximise overall fragment coverage.
Maintained by Sebastian Gibb. Last updated 5 months ago.
immunooncologyinfrastructureproteomicsmassspectrometrycoveragemass-spectrometrytopdown
1 stars 5.08 scorebioc
MSnID:Utilities for Exploration and Assessment of Confidence of LC-MSn Proteomics Identifications
Extracts MS/MS ID data from mzIdentML (leveraging mzID package) or text files. After collating the search results from multiple datasets it assesses their identification quality and optimize filtering criteria to achieve the maximum number of identifications while not exceeding a specified false discovery rate. Also contains a number of utilities to explore the MS/MS results and assess missed and irregular enzymatic cleavages, mass measurement accuracy, etc.
Maintained by Vlad Petyuk. Last updated 5 months ago.
proteomicsmassspectrometryimmunooncology
5.06 score 57 scriptsbioc
ncGTW:Alignment of LC-MS Profiles by Neighbor-wise Compound-specific Graphical Time Warping with Misalignment Detection
The purpose of ncGTW is to help XCMS for LC-MS data alignment. Currently, ncGTW can detect the misaligned feature groups by XCMS, and the user can choose to realign these feature groups by ncGTW or not.
Maintained by Chiung-Ting Wu. Last updated 5 months ago.
softwaremassspectrometrymetabolomicsalignmentcpp
8 stars 4.90 score 3 scriptsbioc
msmsTests:LC-MS/MS Differential Expression Tests
Statistical tests for label-free LC-MS/MS data by spectral counts, to discover differentially expressed proteins between two biological conditions. Three tests are available: Poisson GLM regression, quasi-likelihood GLM regression, and the negative binomial of the edgeR package.The three models admit blocking factors to control for nuissance variables.To assure a good level of reproducibility a post-test filter is available, where we may set the minimum effect size considered biologicaly relevant, and the minimum expression of the most abundant condition.
Maintained by Josep Gregori i Font. Last updated 5 months ago.
immunooncologysoftwaremassspectrometryproteomics
4.86 score 15 scripts 1 dependentsbioc
MatrixQCvis:Shiny-based interactive data-quality exploration for omics data
Data quality assessment is an integral part of preparatory data analysis to ensure sound biological information retrieval. We present here the MatrixQCvis package, which provides shiny-based interactive visualization of data quality metrics at the per-sample and per-feature level. It is broadly applicable to quantitative omics data types that come in matrix-like format (features x samples). It enables the detection of low-quality samples, drifts, outliers and batch effects in data sets. Visualizations include amongst others bar- and violin plots of the (count/intensity) values, mean vs standard deviation plots, MA plots, empirical cumulative distribution function (ECDF) plots, visualizations of the distances between samples, and multiple types of dimension reduction plots. Furthermore, MatrixQCvis allows for differential expression analysis based on the limma (moderated t-tests) and proDA (Wald tests) packages. MatrixQCvis builds upon the popular Bioconductor SummarizedExperiment S4 class and enables thus the facile integration into existing workflows. The package is especially tailored towards metabolomics and proteomics mass spectrometry data, but also allows to assess the data quality of other data types that can be represented in a SummarizedExperiment object.
Maintained by Thomas Naake. Last updated 5 months ago.
visualizationshinyappsguiqualitycontroldimensionreductionmetabolomicsproteomicstranscriptomics
4.74 score 4 scriptsbioc
synapter:Label-free data analysis pipeline for optimal identification and quantitation
The synapter package provides functionality to reanalyse label-free proteomics data acquired on a Synapt G2 mass spectrometer. One or several runs, possibly processed with additional ion mobility separation to increase identification accuracy can be combined to other quantitation files to maximise identification and quantitation accuracy.
Maintained by Laurent Gatto. Last updated 21 days ago.
immunooncologymassspectrometryproteomicsqualitycontrol
4 stars 4.73 score 5 scriptsbioc
bnem:Training of logical models from indirect measurements of perturbation experiments
bnem combines the use of indirect measurements of Nested Effects Models (package mnem) with the Boolean networks of CellNOptR. Perturbation experiments of signalling nodes in cells are analysed for their effect on the global gene expression profile. Those profiles give evidence for the Boolean regulation of down-stream nodes in the network, e.g., whether two parents activate their child independently (OR-gate) or jointly (AND-gate).
Maintained by Martin Pirkl. Last updated 5 months ago.
pathwayssystemsbiologynetworkinferencenetworkgeneexpressiongeneregulationpreprocessing
2 stars 4.60 score 5 scriptsbioc
MAIT:Statistical Analysis of Metabolomic Data
The MAIT package contains functions to perform end-to-end statistical analysis of LC/MS Metabolomic Data. Special emphasis is put on peak annotation and in modular function design of the functions.
Maintained by Pol Sola-Santos. Last updated 5 months ago.
immunooncologymassspectrometrymetabolomicssoftware
4.60 score 20 scriptsbioc
MSstatsQC:Longitudinal system suitability monitoring and quality control for proteomic experiments
MSstatsQC is an R package which provides longitudinal system suitability monitoring and quality control tools for proteomic experiments.
Maintained by Eralp Dogu. Last updated 5 months ago.
softwarequalitycontrolproteomicsmassspectrometry
4.48 score 7 scripts 1 dependentsbioc
cosmiq:cosmiq - COmbining Single Masses Into Quantities
cosmiq is a tool for the preprocessing of liquid- or gas - chromatography mass spectrometry (LCMS/GCMS) data with a focus on metabolomics or lipidomics applications. To improve the detection of low abundant signals, cosmiq generates master maps of the mZ/RT space from all acquired runs before a peak detection algorithm is applied. The result is a more robust identification and quantification of low-intensity MS signals compared to conventional approaches where peak picking is performed in each LCMS/GCMS file separately. The cosmiq package builds on the xcmsSet object structure and can be therefore integrated well with the package xcms as an alternative preprocessing step.
Maintained by David Fischer. Last updated 5 months ago.
immunooncologymassspectrometrymetabolomics
4.48 score 2 scriptsbioc
PRONE:The PROteomics Normalization Evaluator
High-throughput omics data are often affected by systematic biases introduced throughout all the steps of a clinical study, from sample collection to quantification. Normalization methods aim to adjust for these biases to make the actual biological signal more prominent. However, selecting an appropriate normalization method is challenging due to the wide range of available approaches. Therefore, a comparative evaluation of unnormalized and normalized data is essential in identifying an appropriate normalization strategy for a specific data set. This R package provides different functions for preprocessing, normalizing, and evaluating different normalization approaches. Furthermore, normalization methods can be evaluated on downstream steps, such as differential expression analysis and statistical enrichment analysis. Spike-in data sets with known ground truth and real-world data sets of biological experiments acquired by either tandem mass tag (TMT) or label-free quantification (LFQ) can be analyzed.
Maintained by Lis Arend. Last updated 12 days ago.
proteomicspreprocessingnormalizationdifferentialexpressionvisualizationdata-analysisevaluation
2 stars 4.41 score 9 scriptsbioc
msmsEDA:Exploratory Data Analysis of LC-MS/MS data by spectral counts
Exploratory data analysis to assess the quality of a set of LC-MS/MS experiments, and visualize de influence of the involved factors.
Maintained by Josep Gregori. Last updated 5 months ago.
immunooncologysoftwaremassspectrometryproteomics
4.38 score 4 scripts 2 dependents
bioc
protGear:Protein Micro Array Data Management and Interactive Visualization
A generic three-step pre-processing package for protein microarray data. This package contains different data pre-processing procedures to allow comparison of their performance.These steps are background correction, the coefficient of variation (CV) based filtering, batch correction and normalization.
Maintained by Kennedy Mwai. Last updated 5 months ago.
microarrayonechannelpreprocessingbiomedicalinformaticsproteomicsbatcheffectnormalizationbayesianclusteringregressionsystemsbiologyimmunooncologybackground-correctionmicroarray-datanormalisationproteomics-datashinyshinydashboard
1 stars 4.30 score 6 scriptsbioc
flagme:Analysis of Metabolomics GC/MS Data
Fragment-level analysis of gas chromatography-massspectrometry metabolomics data.
Maintained by Mark Robinson. Last updated 5 months ago.
differentialexpressionmassspectrometry
4.30 score 2 scriptsbioc
qPLEXanalyzer:Tools for quantitative proteomics data analysis
Tools for TMT based quantitative proteomics data analysis.
Maintained by Ashley Sawle. Last updated 5 months ago.
immunooncologyproteomicsmassspectrometrynormalizationpreprocessingqualitycontroldataimport
1 stars 4.08 score 9 scriptsbioc
Doscheda:A DownStream Chemo-Proteomics Analysis Pipeline
Doscheda focuses on quantitative chemoproteomics used to determine protein interaction profiles of small molecules from whole cell or tissue lysates using Mass Spectrometry data. The package provides a shiny application to run the pipeline, several visualisations and a downloadable report of an experiment.
Maintained by Bruno Contrino. Last updated 5 months ago.
proteomicsnormalizationpreprocessingmassspectrometryqualitycontroldataimportregression
4.00 score 2 scriptsbioc
MSstatsQCgui:A graphical user interface for MSstatsQC package
MSstatsQCgui is a Shiny app which provides longitudinal system suitability monitoring and quality control tools for proteomic experiments.
Maintained by Eralp Dogu. Last updated 5 months ago.
softwarequalitycontrolproteomicsmassspectrometrygui
4.00 score 1 scriptsbioc
webbioc:Bioconductor Web Interface
An integrated web interface for doing microarray analysis using several of the Bioconductor packages. It is intended to be deployed as a centralized bioinformatics resource for use by many users. (Currently only Affymetrix oligonucleotide analysis is supported.)
Maintained by Colin A. Smith. Last updated 5 months ago.
infrastructuremicroarrayonechanneldifferentialexpression
3.90 score 4 scriptsbioc
ADaCGH2:Analysis of big data from aCGH experiments using parallel computing and ff objects
Analysis and plotting of array CGH data. Allows usage of Circular Binary Segementation, wavelet-based smoothing (both as in Liu et al., and HaarSeg as in Ben-Yaacov and Eldar), HMM, GLAD, CGHseg. Most computations are parallelized (either via forking or with clusters, including MPI and sockets clusters) and use ff for storing data.
Maintained by Ramon Diaz-Uriarte. Last updated 1 months ago.
3.48 score 3 scripts
gefeizhang
statVisual:Statistical Visualization Tools
Visualization functions in the applications of translational medicine (TM) and biomarker (BM) development to compare groups by statistically visualizing data and/or results of analyses, such as visualizing data by displaying in one figure different groups' histograms, boxplots, densities, scatter plots, error-bar plots, or trajectory plots, by displaying scatter plots of top principal components or dendrograms with data points colored based on group information, or visualizing volcano plots to check the results of whole genome analyses for gene differential expression.
Maintained by Wenfei Zhang. Last updated 5 years ago.
3.00 score 3 scripts
moseleybioinformaticslab
ScanCentricPeakCharacterization:Functionality for Characterizing Peaks in Mass Spectrometry in a Scan-Centric Manner
Provides a functions and classes for detecting, characterizing, and integrating peaks in a scan-centric manner from direct-injection mass spectrometry data.
Maintained by Robert M Flight. Last updated 1 years ago.
3.00 score 1 scriptsadafede
sapid:A Strategy to Analyze Plant Extracts Taste In Depth
This package provides the infrastructure to implement a Strategy to Analyze Plant Extracts Taste In Depth.
Maintained by Adriano Rutz. Last updated 6 days ago.
computational metabolomicsnatural extractstaste
2.90 score