Imputation of single-cell transcriptome data enables the reconstruction of networks predictive of breast cancer metastasis
Single-cell transcriptome data provide a unique opportunity to explore the gene networks of a particular cell type. However, insufficient capture rate and high dimensionality of single-cell RNA sequencing (scRNA-seq) data challenge cell-type-specific gene network (CGN) reconstruction. Here, we demon...
Main Authors: | Junha Cha, Michael Lavi, Junhan Kim, Noam Shomron, Insuk Lee |
---|---|
Format: | Article |
Language: | English |
Published: |
Elsevier
2023-01-01
|
Series: | Computational and Structural Biotechnology Journal |
Subjects: | |
Online Access: | http://www.sciencedirect.com/science/article/pii/S2001037023001344 |
Similar Items
-
Single-cell transcriptomics provide insight into metastasis-related subsets of breast cancer
by: Shikun Zhu, et al.
Published: (2023-10-01) -
Evaluating imputation methods for single-cell RNA-seq data
by: Yi Cheng, et al.
Published: (2023-07-01) -
RESCUE: imputing dropout events in single-cell RNA-sequencing data
by: Sam Tracy, et al.
Published: (2019-07-01) -
Integrated analyses of single-cell transcriptomics identify metastasis-associated myeloid subpopulations in breast cancer lung metastasis
by: Zhen Huang, et al.
Published: (2023-07-01) -
SCRABBLE: single-cell RNA-seq imputation constrained by bulk RNA-seq data
by: Tao Peng, et al.
Published: (2019-05-01)