@inproceedings{f9c4cdbc2ad344d2a57ec374132aa430,
title = "Classification of Single Cell Types using Small Sets of Expressed Genes: Comparative Analysis of Supervised Machine Learning Methods",
abstract = "Single cell transcriptomics measures gene expression data of large number of genes, concurrently, from tens of thousands of cells present in a studied biological sample. It is difficult to obtain good classification results due to high data dimensionality and variability of biological states. We performed a preliminary study to assess the feasibility of using supervised machine learning methods to classify peripheral blood mononuclear cell (PBMC) types from single cell gene expression data. We analyzed a large PBMC data set (sim 120,000 PBMC cells), selected 47 genes (from 30698 features) suitable as SML classification features, and performed classification using 20 machine learning algorithms. Data sets represented three sample processing strategies: PBMC separation (two data sets), and experimental cell sorting by (two data sets). The accuracy in 5-class classification among 20 methods was 91-97% (PBMC separation), 97-100% (magnetic-activated cell sorting), and 82-99% (fluorescence-activated cell sorting). Our results indicate the feasibility of supervised machine learning for classification of cells into major PBMC cell types using a small number of classification features from single cell gene expression data.",
keywords = "10x SCT, PBMC, classification, data mining, dimensionality reduction, gene expression, machine learning, transcriptome",
author = "Aleksandar Veljkovic and Mirjana Maljkovic and Nenad Mitic and Sasa Malkov and Minjie Lyu and Xin Lin and Marek Michalewicz and Guanglan Zhang and Vladimir Brusic",
note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 2021 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2021 ; Conference date: 09-12-2021 Through 12-12-2021",
year = "2021",
doi = "10.1109/BIBM52615.2021.9669844",
language = "English",
series = "Proceedings - 2021 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2021",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "3322--3326",
editor = "Yufei Huang and Lukasz Kurgan and Feng Luo and Hu, {Xiaohua Tony} and Yidong Chen and Edward Dougherty and Andrzej Kloczkowski and Yaohang Li",
booktitle = "Proceedings - 2021 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2021",
address = "United States",
}