Prediction of cell position using single-cell transcriptomic data: an iterative procedure.
F1000Res
; 8: 1775, 2019.
Article
in En
| MEDLINE
| ID: mdl-32399185
ABSTRACT
Single-cell sequencing reveals cellular heterogeneity but not cell localization. However, by combining single-cell transcriptomic data with a reference atlas of a small set of genes, it would be possible to predict the position of individual cells and reconstruct the spatial expression profile of thousands of genes reported in the single-cell study. With the purpose of developing new algorithms, the Dialogue for Reverse Engineering Assessments and Methods (DREAM) consortium organized a crowd-sourced competition known as DREAM Single Cell Transcriptomics Challenge (SCTC). Within this context, we describe here our proposed procedures for adequate reference genes selection, and an iterative procedure to predict spatial expression profile of other genes.
Key words
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Algorithms
/
Gene Expression Profiling
/
Transcriptome
Type of study:
Prognostic_studies
/
Risk_factors_studies
Language:
En
Journal:
F1000Res
Year:
2019
Document type:
Article
Affiliation country:
Argentina