Article (Scientific journals)
Gene selection for optimal prediction of cell position in tissues from single-cell transcriptomics
Tanevski, Jovan; Nguyen, Thin; Truong, Buu et al.
2020In Life Science Alliance, 3 (11), p. 202000867
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Keywords :
transcriptomics; single-cell; prediction; cell position; 3D; gene selection; Drosophila; scRNAseq; challenge
Abstract :
[en] Single-cell RNA-seq (scRNAseq) technologies are rapidly evolving. While very informative, in standard scRNAseq experiments the spatial organization of the cells in the tissue of origin is lost. Conversely, spatial RNA-seq technologies designed to maintain cell localization have limited throughput and gene coverage. Mapping scRNAseq to genes with spatial information increases coverage while providing spatial location. However, methods to perform such mapping have not yet been benchmarked. To fill this gap, we organized the DREAM Single-Cell Transcriptomics challenge focused on the spatial reconstruction of cells from the Drosophila embryo from scRNAseq data, leveraging as silver standard, genes with in situ hybridization data from the Berkeley Drosophila Transcription Network Project reference atlas. The 34 participating teams used diverse algorithms for gene selection and location prediction, while being able to correctly localize clusters of cells. Selection of predictor genes was essential for this task. Predictor genes showed a relatively high expression entropy, high spatial clustering and included prominent developmental genes such as gap and pair-rule genes and tissue markers. Application of the Top-10 methods to a zebrafish embryo dataset yielded similar performance and statistical properties of the selected genes than in the Drosophila data. This suggests that methods developed in this challenge are able to extract generalizable properties of genes that are useful to accurately reconstruct the spatial arrangement of cells in tissues.
Research center :
- Luxembourg Centre for Systems Biomedicine (LCSB): Biomedical Data Science (Glaab Group)
- Luxembourg Centre for Systems Biomedicine (LCSB): Bioinformatics Core (R. Schneider Group)
Disciplines :
Life sciences: Multidisciplinary, general & others
Biotechnology
Author, co-author :
Tanevski, Jovan
Nguyen, Thin
Truong, Buu
Karaiskos, Nikolaos
Eren, Mehmet
Zhang, Xinyu
Shu, Chang
Hu, Ying
Pham, Hoang V. V.
Li, Xiaomei
Le, Thuc
Tarca, Adi
Bhatti, Gaurav
Romero, Roberto
Karathanasis, Nestoras
Loher, Phillipe
Chen, Yang
Ouyang, Zhengqing
Mao, Disheng
Zhang, Yuping
Zand, Maryam
Ruan, Jianhua
Hafemeister, Christoph
Qiu, Peng
Tran, Duc
Nguyen, Tin
Gabor, Attila
Yu, Thomas
Glaab, Enrico  ;  University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB)
Krause, Roland  ;  University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB)
Banda, Peter ;  University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB)
Stolovitzky, Gustavo
Rajewsky, Nikolaus
Saez-Rodriguez, Julio
More authors (24 more) Less
External co-authors :
yes
Language :
English
Title :
Gene selection for optimal prediction of cell position in tissues from single-cell transcriptomics
Publication date :
2020
Journal title :
Life Science Alliance
ISSN :
2575-1077
Publisher :
Life Science Alliance (LLC), Woodbury, United States
Volume :
3
Issue :
11
Pages :
e202000867
Peer reviewed :
Peer Reviewed verified by ORBi
Focus Area :
Systems Biomedicine
Commentary :
in press
Available on ORBilu :
since 01 September 2020

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