scMoC: single-cell multi-omics clustering

被引:3
作者
Eltager, Mostafa [1 ]
Abdelaal, Tamim [1 ,2 ,3 ]
Mahfouz, Ahmed [1 ,2 ,4 ]
Reinders, Marcel J. T. [1 ,2 ]
机构
[1] Delft Univ Technol, Delft Bioinformat Lab, NL-2628XE Delft, Netherlands
[2] Leiden Univ Med Ctr, Leiden Computat Biol Ctr, NL-2333ZC Leiden, Netherlands
[3] Leiden Univ Med Ctr, Dept Radiol, Div Image Proc, NL-2333ZC Leiden, Netherlands
[4] Leiden Univ Med Ctr, Dept Human Genet, NL-2333ZC Leiden, Netherlands
来源
BIOINFORMATICS ADVANCES | 2022年 / 2卷 / 01期
基金
欧盟地平线“2020”;
关键词
D O I
10.1093/bioadv/vbac011
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
Motivation Single-cell multi-omics assays simultaneously measure different molecular features from the same cell. A key question is how to benefit from the complementary data available and perform cross-modal clustering of cells.Results We propose Single-Cell Multi-omics Clustering (scMoC), an approach to identify cell clusters from data with comeasurements of scRNA-seq and scATAC-seq from the same cell. We overcome the high sparsity of the scATAC-seq data by using an imputation strategy that exploits the less-sparse scRNA-seq data available from the same cell. Subsequently, scMoC identifies clusters of cells by merging clusterings derived from both data domains individually. We tested scMoC on datasets generated using different protocols with variable data sparsity levels. We show that scMoC (i) is able to generate informative scATAC-seq data due to its RNA-guided imputation strategy and (ii) results in integrated clusters based on both RNA and ATAC information that are biologically meaningful either from the RNA or from the ATAC perspective.Availability and implementation The data used in this manuscript is publicly available, and we refer to the original manuscript for their description and availability. For convience sci-CAR data is available at NCBI GEO under the accession number of GSE117089. SNARE-seq data is available at NCBI GEO under the accession number of GSE126074. The 10X multiome data is available at the following link https://www.10xgenomics.com/resources/datasets/pbmc-from-a-healthy-donor-no-cell-sorting-3-k-1-standard-2-0-0.Supplementary information are available at Bioinformatics Advances online.
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页数:8
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