Alpaca. A Simplified and Reproducible Python‐Based Pipeline for Absolute Proteome Quantification Data Mining

ABSTRACT The accurate construction of computational models in systems biology heavily relies on the availability of quantitative proteomics data, specifically, absolute protein abundances. However, the complex nature of proteomics data analysis necessitates specialised expertise, making the integrat...

Full description

Saved in:
Bibliographic Details
Published in:Proteomics (Weinheim) Vol. 25; no. 9-10; pp. e202400417 - n/a
Main Authors: Ferrero‐Bordera, Borja, Becher, Dörte, Maaß, Sandra
Format: Journal Article
Language:English
Published: Germany Wiley Subscription Services, Inc 01.05.2025
John Wiley and Sons Inc
Subjects:
absolute proteome quantification
Animals
Availability
Biology
Data analysis
Data mining
Data Mining - methods
Data processing
Graphical user interface
Mathematical models
Modular structures
open source
protein abundances
Proteins
Proteome - analysis
Proteomes
Proteomics
Proteomics - methods
proteomics analysis
Python
Reproducibility
Reproducibility of Results
Robustness
Software
Technical Brief
User-Computer Interface
open source
proteomics
data mining
protein abundances
Python
absolute proteome quantification
proteomics analysis
ISSN:1615-9853, 1615-9861, 1615-9861
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:ABSTRACT The accurate construction of computational models in systems biology heavily relies on the availability of quantitative proteomics data, specifically, absolute protein abundances. However, the complex nature of proteomics data analysis necessitates specialised expertise, making the integration of this data into models challenging. Therefore, the development of software tools that ease the analysis of proteomics data and bridge between disciplines is crucial for advancing the field of systems biology. We developed an open access Python‐based software tool available either as downloadable library or as web‐based graphical user interface (GUI). The pipeline simplifies the extraction and calculation of protein abundances from unprocessed proteomics data, accommodating a range of experimental approaches based on label‐free quantification. Our tool was conceived as a versatile and robust pipeline designed to ease and simplify data analysis, thereby improving reproducibility between researchers and institutions. Moreover, the robust modular structure of Alpaca allows its integration with other software tools.
Bibliography:This study was funded by the People Programme (Marie Skłodowska‐Curie Actions) of the European Union's Horizon 2020 Programme under REA grant agreement no. 813979 (SECRETERS).
Funding
ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
content type line 23
Funding: This study was funded by the People Programme (Marie Skłodowska‐Curie Actions) of the European Union's Horizon 2020 Programme under REA grant agreement no. 813979 (SECRETERS).
ISSN:1615-9853
1615-9861
1615-9861
DOI:10.1002/pmic.202400417