c-CSN:Single-cell RNA Sequencing Data Analysis by Conditional Cell-specific Network
- Author:
Li LIN
1
,
2
;
Dai HAO
;
Fang ZHAOYUAN
;
Chen LUONAN
Author Information
1. Key Laboratory of Systems Biology,Shanghai Institute of Biochemistry and Cell Biology,Center for Excellence in Molecular Cell Science,Chinese Academy of Sciences,Shanghai 200031,China
2. University of Chinese Academy of Sciences,Beijing 100049,China
- Keywords:
Network flow entropy;
Cell-specific network;
Single-cell network;
Direct association;
Conditional independence
- From:
Genomics, Proteomics & Bioinformatics
2021;19(2):319-329
- CountryChina
- Language:Chinese
-
Abstract:
The rapid advancement of single-cell technologies has shed new light on the complex mechanisms of cellular heterogeneity.However,compared to bulk RNA sequencing (RNA-seq),single-cell RNA-seq (scRNA-seq) suffers from higher noise and lower coverage,which brings new computational difficulties.Based on statistical independence,cell-specific network (CSN) is able to quantify the overall associations between genes for each cell,yet suffering from a problem of overestimation related to indirect effects.To overcome this problem,we propose the c-CSN method,which can construct the conditional cell-specific network (CCSN) for each cell.c-CSN method can measure the direct associations between genes by eliminating the indirect associations.c-CSN can be used for cell clustering and dimension reduction on a network basis of single cells.Intuitively,each CCSN can be viewed as the transformation from less "reliable" gene expression to more "reliable" gene-gene associations in a cell.Based on CCSN,we further design network flow entropy (NFE) to estimate the differentiation potency of a single cell.A number of scRNA-seq data-sets were used to demonstrate the advantages of our approach.1) One direct association network is generated for one cell.2) Most existing scRNA-seq methods designed for gene expression matrices are also applicable to c-CSN-transformed degree matrices.3) CCSN-based NFE helps resolving the direction of differentiation trajectories by quantifying the potency of each cell.c-CSN is publicly available at https://github.com/LinLi-0909/c-CSN.
