Application summary

This application provides an interactive user interface for the R package tidyproteomics. Users may upload their protein- or peptide-level data for abundance subsetting, contaminant removal, abundance normalization, differential expression analysis, and ontology enrichment.

Please proceed to the 'Data Input and Summary' tab to begin your analysis. The analysis options available for your dataset will populate the sidebar after you have uploaded your data.

Application features

A detailed tutorial on using this application is available on its dedicated documentation webpage.

Data input and information

Application introduction

The current page describes all the features contained in the application.

Data input and summary

Users may upload an Excel file containing peptide- or protein-level data outputs from Proteome Discoverer and MaxQuant searches. After the file is processed into a tidyproteomics object, the user may view its attributes, such as annotation information, sample identifiers, and raw protein abundances.

Data preprocessing

Data subsetting and summary

Users may subset their data by any of the qualitative or quantitative variables present across the experiments, accounting, or annotation attributes of the data set. Users may also specify a text pattern for removing contaminant proteins from their data. Finally, sample groups can also be reassigned or renamed using the interactive spreadsheet.

Abundance normalization

Once data are uploaded and optionally subsetted, users can specify a method for imputing missing protein abundance values. Imputation can be specified to occur before or after protein abundance normalization, which can be performed using the methods chosen by the user in this tab.

Peptide collapse

This tab appears once peptide-level data are uploaded to the application. Peptide abundances are transformed into protein abundances by using the collapse function of tidyproteomics. Please note that the collapse of normalized peptide abundances into protein-level data is not currently supported. The unprocessed dataset will be used if the data are not modified in the data subsetting tab.

Data analysis

Expression analysis

Users may conduct differential expression analysis using the preprocessed protein abundance values by specifying sample groups for comparison and a statistical method for estimating fold changes and p-values. Results are displayed in an interactive volcano or proportional plot and an accompanying table.

Enrichment analysis

This tab appears after conducting differential expression analysis. Users may select a group comparison and examine the differential expression data for enrichment of terms from the user-specified ontology. Users can specify either the GSEA algorithm or a Wilcoxon rank sum comparison for conducting this analysis.

Copyright © 2023, California Institute of Technology (Caltech), based on support from the Institute for Collaborative Biotechnologies through cooperative agreement W911NF-19-2-0026 from the U.S. Army Research Office. The content of the information does not necessarily reflect the position or the policy of the Government, and no official endorsement should be inferred.

All rights reserved.

Table upload

Select a data type

Select an analyte type

—or—

Use example dataset?

tidyproteomics object summary

Please upload a data table to use this feature

Provide a contaminant pattern

Subsetting parameters

Subset data by user pattern?

Please upload a data table to use this feature

Provide a value for subsetting

Select a value for subsetting

Remove contamination by subsetting with pattern?

Provide a contaminant pattern

Reassign sample groups? Names must not start with a number.

Please upload a data table to use this feature

Provide a contaminant pattern

Normalization selection

Select normalization methods for evaluation

Automatically select optimal normalization method?

Select the user-specified normalization method

Impute missing values?

Impute before or after normalization?

Select a function for imputation

Select a method for imputation

Abundance boxplots

Abundance CVs and dynamic range

Principal component analysis (PCA)

Clustered heatmap

Abundance export

Collapse parameters

Select assignment method

Differential expression parameters

Select a sample group (ratio numerator)

Select a sample group (ratio denominator)

Select a statistical method

Show colored fold change panels?

Show fold change thresholds?

Show ratio scale?

Sigificance column

Significance threshold

Fold change threshold

Upregulated protein color

Downregulated protein color

Show colored fold change panels?

Show fold change thresholds?

Show ratio scale?

Sigificance column

Proportion threshold

Significance threshold

Fold change threshold

Upregulated protein color

Downregulated protein color

Select an x-axis variable

Select a y-axis variable

Select a color variable

Choose a color

Set marker opacity

Select a size variable

Differential expression table

Display all quantitative information?

Filter by adjusted p-value?

accepted adj. p-values

Filter by log2(foldchange)?

excluded log2(foldchange) values

Enrichment parameters

Select an existing comparison

Select ontology for annotation enrichment

Select an enrichment method

Application summary

Application features

Application introduction

Data input and summary

Data subsetting and summary

Abundance normalization

Peptide collapse

Expression analysis

Enrichment analysis

Table upload

tidyproteomics object summary

‌

Subsetting parameters

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Normalization selection

Abundance boxplots

Abundance CVs and dynamic range

Principal component analysis (PCA)

Clustered heatmap

Abundance export

Collapse parameters

Differential expression parameters

‌

Differential expression table

Enrichment parameters

Annotation enrichment plot

Annotation enrichment table