An app by B. Ferrero-Bordera from Microbial Proteomics (Uni Greifswald)

Getting started

Access the GUI in the following link:

🔗 alpaca.streamlit.app

This is a GUI from the Python package Alpaca_proteomics. The app aims to facilitate the analysis of proteomics samples for Absolute Proteome Quantification based on protein standards.

Cite us

Stay tuned, the paper is submitted.

Example datasets

Example datasets are available in the following folder.

• Enriched_example.txt: Exoproteome dataset from Ferrero-Bordera et al. 2024. Microbiology Spectrum
• Membrane_example.txt: Membrane proteome dataset from Antelo-Varela et al. 2019. Anal. Chem.

Tutorial

Alpaca GUI tutorial

Alpaca is a GUI optimised for the analysis and quantification of proteomics samples using protein standards (e.g., UPS2). It uses the Python pipeline Alpaca_proteomics for quantifying Mass Spectrometry (MS)-based proteomics samples.

When accessing the GUI, a short description of the preferable workflow for the pipeline is shown in the main body. In the side bar, an uploader widget allows the users to import their ProteinGroups. CSV, TXT and Excel files are compatible with the software. Below the widget, different example datasets can be selected to explore the GUI capabilities.

Sample names and replicates for each studied condition are inferred by the software based on the given names during the search on MaxQuant.

After uploading the ProteinGroups file, the GUI changes to the data analysis page. This page consists of two main parts, the body and the sidebar.

• The GUI sidebar controls quantification parameters as desired MS intensity method, normalization and protein standards. The sidebar contains 2 main parts (Data preprocessing and Quantification standards). The desired data processing parameters can be chosen in the Data preprocessing section. This includes removal of contaminants, intensity normalization and data formatting. Additionally, the Quantification standards section allows to select the used protein standards for quantification and the added amounts. By default, it is set for UPS2, but custom standards can be added).

• The GUI body which is divided into 3 parts (Experimental set-up, Data visualization and Your data) allows the user to add details on the experiment and visualize the data. Details on the sample preparation can be added to the Experimental set-up tab. Summary statistics of the data and its quantification can be explored in the Data visualization tab. Finally, Your data corresponds to the quantified proteins in a tabular format ready to be exported.

GUI side bar

Data preprocessing

• Data cleaning: If selected, proteins tagged as contaminants, decoys or reverse identifications are removed. It can be selected below which ones to remove or keep if necessary. Enabled by default.
• Data formatting: Formats the data for the pipeline calculations. Necessary for the pipeline. If not selected, the data can only be cleaned as specified above and exported. Enabled by default.
• Label-Free Quantification Method: The desired intensity-based method can be selected in this tab. The intensity methods shown are based on the ones identified in the provided dataset. By default, iBAQ is selected if it is present in the dataset.
• Normalization: Three methods are implemented in Alpaca for intensity normalization. Median, relative and quantile normalization. By default is None.

Quantification standards

Absolute quantification using Alpaca is optimised for label-free methods, relying on the addition of a set of anchor proteins at a known amount. By default, UPS2 are set as anchor proteins. The user can add custom anchor proteins following the format described in Table 1.

Table 1. Format for the file describing the stock solution of anchor proteins.

Accession	MW (kDa)	Amount (fmol)
P02768	10.1	50
Q9Y6K9	65.8	100
P05067	32.5	25
O75475	48.2	75
Q00653	20.9	30

GUI body

Experimental set-up

This tab controls the sample preparation. It is an optional input in case the user wants to trace back to the original amount in the samples, rather than just quantifying what was measured in the Mass Spectrometer.

Sample preparation

Table 2. Example of the input table to define the parameters used for sample parameters. An example table can be generated in the GUI based on the added conditions. This example table can be exported as a template and edited to be imported later into the GUI.

Condition	SampleVolume	ProteinConcentration	AmountMS	CellsPerML	TotalCultureVolume	ProteinSRM	fmolSRM	Enrichment	EnrichmentDirection	StdDilution	StdVolume
Cond1_t0	2.31	2.99	9.67	4.54	7.54	TNAMLN	4.44	False	Down	3.96	1.22
Cond2_t1	2.50	0.20	4.10	5.13	2.62	AJFVYC	4.85	True	Down	2.43	1.51
Cond3_t2	7.38	6.56	2.77	3.66	3.80	BYEKSC	9.71	True	Down	5.71	8.53

• Condition: Condition in which the parameters were applied.
• SampleVolume: Protein extract volume (µL) used for protein digestion.
• ProteinConcentration: Determined protein concentration (µg/µl) in the sample.
• AmountMS: Protein amount (µg) injected in the MS.
• CellsPerML: Measured cells per mL of culture.
• TotalCultureVolume: Total cultivation volume (µL).
• ProteinSRM Optional: If the enrichment of a subcellular fraction has been calculated using targeted proteomics (SRM). This corresponds to the accession of measured protein in SRM to calculate the enrichment.
• fmolSRM Optional: If the enrichment of a subcellular fraction has been calculated using targeted proteomics (SRM). Fmol of the proteins measured in the targeted proteomics measurements.
• Enrichment Optional: Boolean (True or False). Samples that have been enriched should be specified as True
• EnrichmentDirection Optional: UP or DOWN.
• StdDilution Optional: This parameter specifies how many times the stock solution of enrichment standards has been diluted before adding it to the sample. If the standards were not diluted before addition, specify 1. Only used when the enrichment is calculated through the function alpaca.gathers() details of the preparation of the used proteins should be added.
• StdVolume Optional: Volume of enrichment standards (µL) added to the sample. Only used in case the enrichment is calculated through the function alpaca.gathers() details of the preparation of the used proteins should be added.

Proteome fraction enrichment (Optional)

In case the sample preparation includes the enrichment of a subproteomic fraction and protein standards have been used to quantify this enrichment step, the standards can be uploaded in this section. As in the sample preparation tab, a template can be generated and downloaded to edit. The GUI accepts the format described in Table 3.

Table 3. Example of the enrichment standards input.

Accession	MW (kDa)	StdConcentration (µg/µl)
P02768	10.1	2.5
Q9Y6K9	65.8	0.8
P05067	32.5	1.2
O75475	48.2	3.0
Q00653	20.9	2.0

Data visualization

This tab allows to explore some summary statistics of the data. As it is the number of proteins quantified (Quantified proteins) per sample and summary statistics of the measured intensities per sample represented as a boxplot (intensities). Additionally, principal component analysis (PCA) and intensity distribution (Distribution plot) were added to the assessment of the sample quality. The fitting of calibration standards can be visualized in the Calibration curve. Finally, a heatmap can be drawn and exported if desired.

Your Data

This section corresponds to the quantified data allowing the user to export it for further analysis. The data is exported as CSV. The data can be pivoted if the export format is not the desired, as by default it specified a row per protein quantified in each sample. Quantified data can also be filtered and sorted to export just a selected set of proteins.