Disease Classification in Metagenomics with 2D Embeddings and Deep Learning
Nguyen, Thanh Hai; Prifti, Edi; Chevaleyre, Yann; Sokolovska, Nataliya; Zucker, Jean-Daniel (2018), Disease Classification in Metagenomics with 2D Embeddings and Deep Learning, La Conférence sur l'Apprentissage automatique (CAp), 2018-06, Rouen, FRANCE
TypeCommunication / Conférence
External document linkhttps://hal.sorbonne-universite.fr/hal-01819205
Conference titleLa Conférence sur l'Apprentissage automatique (CAp)
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Abstract (EN)Deep learning (DL) techniques have shown unprecedented success when applied to images, waveforms, and text. Generally, when the sample size (N) is much bigger than the number of features (d), DL often out-performs other machine learning (ML) techniques, often through the use of Convolutional Neural Networks (CNNs). However, in many bioinformatics fields (including metagenomics), we encounter the opposite situation where d is significantly greater than N. In these situations, applying DL techniques would lead to severe over-fitting. Here we aim to improve classification of various diseases with metagenomic data through the use of CNNs. For this we proposed to represent metagenomic data as images. The proposed Met2Img approach relies on taxonomic and t-SNE embeddings to transform abundance data into " synthetic images ". We applied our approach to twelve benchmark data sets including more than 1400 metagenomic samples. Our results show significant improvements over the state-of-the-art algorithms (Random Forest (RF), Support Vector Machine (SVM)). We observe that the integration of phylogenetic information alongside abundance data improves classification. The proposed approach is not only important in classification setting but also allows to visualize complex metagenomic data. The Met2Img is implemented in Python.
Subjects / KeywordsMachine Learning for Health; classification; metagenomics; deep learning; visualization
Showing items related by title and author.
Thanh Hai, Nguyen; Chevaleyre, Yann; Prifti, Edi; Sokolovska, Nataliya; Zucker, Jean-Daniel (2017) Communication / Conférence