Man pages for MeenaChoi/MSstats
Protein Significance Analysis in DDA, SRM and DIA for Label-free or Label-based Proteomics Experiments
| checkRepeatedDesign | Check if data represents repeated measurements design |
| dataProcess | Process MS data: clean, normalize and summarize before... |
| dataProcessPlots | Visualization for explanatory data analysis |
| DDARawData | Example dataset from a label-free DDA, a controlled spike-in... |
| DDARawData.Skyline | Example dataset from a label-free DDA, a controlled spike-in... |
| designSampleSize | Planning future experimental designs of Selected Reaction... |
| designSampleSizePlots | Visualization for sample size calculation |
| DIANNtoMSstatsFormat | Import Diann files |
| DIARawData | Example dataset from a label-free DIA, a group comparison... |
| DIAUmpiretoMSstatsFormat | Import DIA-Umpire files |
| dot-addCoverageInfo | Add coverage information to a data.table |
| dot-addModelInformation | Add model information |
| dot-addModelVariances | Add model variances |
| dot-addNInformativeInfo | Add information about number of informative features |
| dot-addNoisyFlag | Add flag for noisy features |
| dot-addOutlierCutoff | Add outlier cutoff |
| dot-addOutlierInformation | Add flag for outlier |
| dot-addSurvivalPredictions | Get predicted values from a survival model |
| dot-adjustLRuns | Adjust summarized abundance based on the heavy channel |
| dot-calculateOutlierCutoff | Calculate cutoff to label outliers |
| dot-calculatePower | Power calculation |
| dot-calculateProteinVariance | Calculate protein variances |
| dot-checkContrastMatrix | Check if contrast matrix includes all conditions |
| dot-checkDataProcessParams | Check validity of parameters to dataProcess function |
| dot-checkExperimentDesign | Check if a given column exists in the data |
| dot-checkGCPlotsInput | Check groupComparisonPlots parameters |
| dot-checkGroupComparisonInput | Check if groupComparison input was processed by the... |
| dot-checkSingleFeature | Check if data has less than two features |
| dot-checkSingleLabelProteins | Check if there are proteins with a single label in a labeled... |
| dot-checkSingleSubject | Check if there is only single subject |
| dot-checkTechReplicate | Check if there are technical replicates |
| dot-checkUnProcessedDataValidity | Check validity of data that were not processed by MSstats... |
| dot-countInformative | Count informative features |
| dot-countMissingPercentage | Count percentage of missing values in given conditions |
| dot-documentFunction | A dummy function to store shared documentation items. |
| dot-finalizeInput | Add summary statistics to dataProcess output |
| dot-finalizeLinear | Summary statistics for linear model-based summarization |
| dot-finalizeTMP | Summary statistics for output of TMP-based summarization |
| dot-fitHuber | Wrapper to fit robust linear model for one protein |
| dot-fitLinearModel | Fit a linear model |
| dot-fitModelForGroupComparison | Choose a model type (fixed/mixed effects) and fit it for a... |
| dot-fitModelSingleProtein | Fit model and perform group comparison for a single protein |
| dot-fitTukey | Fit tukey median polish for a data matrix |
| dot-flagLowCoverage | Flag for low coverage features |
| dot-flagUninformativeSingleLabel | Flag uninformative features |
| dot-getAllComparisons | Get all comparisons for a single protein and a contrast... |
| dot-getColorKeyGGPlot2 | Create colorkey for ggplot2 heatmap |
| dot-getColorKeyPlotly | Create colorkey for plotly heatmap |
| dot-getContrast | Create a contrast for a model with only group as a fixed... |
| dot-getContrastLabels | Get labels for contrasts |
| dot-getEmptyComparison | Comparison output when there are measurements only in a... |
| dot-getFeatureVariances | Calculate variances of features |
| dot-getMedian | Get median of protein abundances for a given label |
| dot-getMedianSigmaSubject | Get median per subject or group by subject |
| dot-getMin | Utility function: get 0.99 * minimum of non-missing values |
| dot-getModelParameters | Get params (coefficients, covariance matrix, degrees of... |
| dot-getNonMissingFilter | Identify non-missing values |
| dot-getNonMissingFilterStats | Get a logical vector for non-missing values to calculate... |
| dot-getNumSample | Get sample size |
| dot-getSingleProteinForProfile | Get data for a single protein to plot |
| dot-getVarComponent | Get variances from models fitted by the groupComparison... |
| dot-getWideTable | Utility function for quantile normalization - get table in... |
| dot-getYaxis | Get name for y-axis |
| dot-groupComparisonWithMultipleCores | Perform group comparison per protein in parallel |
| dot-groupComparisonWithSingleCore | Perform group comparison per protein iteratively with a... |
| dot-handleEmptyConditions | Handle contrast when some of the conditions are missing |
| dot-handleSingleContrast | Group comparison for a single contrast |
| dot-isSummarizable | Check if a protein can be summarized with TMP |
| dot-logDatasetInformation | Log information about feature-level data |
| dot-logMissingness | Log information about missing data |
| dot-logSingleLabeledProteins | Print proteins with a single label to the log file |
| dot-logSummaryStatistics | Print summary statistics to the log file |
| dot-makeComparison | Create comparison plot |
| dot-makeConditionPlot | Make condition plot |
| dot-makeFactorColumns | Make factor columns where needed |
| dot-makeHeatmapPlotly | Create heatmap |
| dot-makeProfilePlot | Create profile plot |
| dot-makeQCPlot | Make QC plot |
| dot-makeSummaryProfilePlot | Make summary profile plot |
| dot-makeVolcano | Create a volcano plot |
| dot-nicePrint | Print a table nicely |
| dot-normalizeGlobalStandards | Normalization based on standards |
| dot-normalizeMedian | Median normalization |
| dot-normalizeQuantile | Quantile normalization based on the 'preprocessCore' package |
| dot-onLoad | Set default logging object when package is loaded |
| dot-plotComparison | Preprocess data for comparison plots and create them |
| dot-plotHeatmap | Prepare data for heatmaps and plot them |
| dot-plotVolcano | Preprocess data for volcano plots and create them |
| dot-prepareForDataProcess | Check validity of data already processed by MSstats converter |
| dot-prepareLinear | Prepare feature-level data for linear summarization |
| dot-prepareSingleProteinForGC | Prepare data for a single protein for group comparison |
| dot-prepareSummary | Prepare feature-level data for summarization |
| dot-prepareTMP | Prepare feature-level data for TMP summarization |
| dot-preProcessIntensities | Create ABUNDANCE column and log-transform intensities |
| dot-quantileNormalizationSingleLabel | Quantile normalization for a single label |
| dot-replaceZerosWithNA | Utility function for normalization: replace 0s by NA |
| dot-runTukey | Fit Tukey median polish |
| dot-saveSessionInfo | Save information about R session to sessionInfo.txt file. |
| dot-saveTable | Save a data table to a file |
| dot-selectHighQualityFeatures | Select features of high quality |
| dot-selectTopFeatures | Select features with highest average abundance |
| dot-setCensoredByThreshold | Set censored values based on minimum in run/feature/run or... |
| dot-updateColumnsForProcessing | Create columns for data processing |
| dot-updateUnequalVariances | Adjust model for unequal variances |
| example_SDRF | Example SDRF. |
| extractSDRF | Extract experimental design from MSstats format into SDRF... |
| FragPipetoMSstatsFormat | Import FragPipe files |
| getProcessed | Get feature-level data to be used in the... |
| getSamplesInfo | Get information about number of measurements for each group |
| getSelectedProteins | Get proteins based on names or integer IDs |
| groupComparison | Whole plot testing |
| groupComparisonPlots | Visualization for model-based analysis and summarizing... |
| groupComparisonQCPlots | Visualization for model-based quality control in fitting... |
| makePeptidesDictionary | Prepare a peptides dictionary for global standards... |
| MaxQtoMSstatsFormat | Import MaxQuant files |
| modelBasedQCPlots | Visualization for model-based quality control in fitting... |
| MSstatsContrastMatrix | Create a contrast matrix for groupComparison function |
| MSstatsGroupComparison | Group comparison |
| MSstatsGroupComparisonOutput | Create output of group comparison based on results for... |
| MSstatsGroupComparisonSingleProtein | Group comparison for a single protein |
| MSstatsHandleMissing | Handle censored missing values |
| MSstatsMergeFractions | Re-format the data before feature selection |
| MSstatsNormalize | Normalize MS data |
| MSstatsPrepareForDataProcess | Prepare data for processing by 'dataProcess' function |
| MSstatsPrepareForGroupComparison | Prepare output for dataProcess for group comparison |
| MSstatsPrepareForSummarization | Prepare feature-level data for protein-level summarization |
| MSstatsSelectFeatures | Feature selection before feature-level data summarization |
| MSstatsSummarizationOutput | Post-processing output from MSstats summarization |
| MSstatsSummarize | Feature-level data summarization |
| MSstatsSummarizeSingleLinear | Linear model-based summarization for a single protein |
| MSstatsSummarizeSingleTMP | Tukey Median Polish summarization for a single protein |
| MSstatsSummarizeWithMultipleCores | Feature-level data summarization with multiple cores |
| MSstatsSummarizeWithSingleCore | Feature-level data summarization with 1 core |
| OpenMStoMSstatsFormat | Import OpenMS files |
| OpenSWATHtoMSstatsFormat | Import OpenSWATH files |
| PDtoMSstatsFormat | Import Proteome Discoverer files |
| ProgenesistoMSstatsFormat | Import Progenesis files |
| quantification | Protein sample quantification or group quantification |
| savePlot | Save a plot to pdf file |
| SDRFtoAnnotation | Convert SDRF experimental design file into an MSstats... |
| SkylinetoMSstatsFormat | Import Skyline files |
| SpectronauttoMSstatsFormat | Import Spectronaut files |
| SRMRawData | Example dataset from a SRM experiment with stable isotope... |
| theme_msstats | Theme for MSstats plots |
| validateAnnotation | Check if annotation matches intended experimental design |
