PERCEPTRON: an open-source GPU-accelerated proteoform identification pipeline for top-down proteomics

Author:

Khalid Muhammad Farhan1,Iman Kanzal1,Ghafoor Amna1,Saboor Mujtaba1,Ali Ahsan1,Muaz Urwa1,Basharat Abdul Rehman1ORCID,Tahir Taha1,Abubakar Muhammad1,Akhter Momina Amer1,Nabi Waqar2,Vanderbauwhede Wim2,Ahmad Fayyaz3,Wajid Bilal456,Chaudhary Safee Ullah1ORCID

Affiliation:

1. Biomedical Informatics Research Laboratory, Department of Biology, Lahore University of Management Sciences, Lahore, Pakistan

2. School of Computing Science, University of Glasgow, Glasgow, G12 8QQ, UK

3. Department of Statistics, University of Gujrat, Gujrat, Pakistan

4. Department of Electrical Engineering, University of Engineering and Technology, Lahore, Pakistan

5. Department of Computer Science, University of Management and Technology, Lahore, Pakistan

6. Division of Research and Development, Sabz-Qalam, Lahore, Pakistan

Abstract

Abstract PERCEPTRON is a next-generation freely available web-based proteoform identification and characterization platform for top-down proteomics (TDP). PERCEPTRON search pipeline brings together algorithms for (i) intact protein mass tuning, (ii) de novo sequence tags-based filtering, (iii) characterization of terminal as well as post-translational modifications, (iv) identification of truncated proteoforms, (v) in silico spectral comparison, and (vi) weight-based candidate protein scoring. High-throughput performance is achieved through the execution of optimized code via multiple threads in parallel, on graphics processing units (GPUs) using NVidia Compute Unified Device Architecture (CUDA) framework. An intuitive graphical web interface allows for setting up of search parameters as well as for visualization of results. The accuracy and performance of the tool have been validated on several TDP datasets and against available TDP software. Specifically, results obtained from searching two published TDP datasets demonstrate that PERCEPTRON outperforms all other tools by up to 135% in terms of reported proteins and 10-fold in terms of runtime. In conclusion, the proposed tool significantly enhances the state-of-the-art in TDP search software and is publicly available at https://perceptron.lums.edu.pk. Users can also create in-house deployments of the tool by building code available on the GitHub repository (http://github.com/BIRL/Perceptron).

Funder

HEC

Ignite

TWAS

Publisher

Oxford University Press (OUP)

Subject

Genetics

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