Open Peer Review Any reports and responses or comments on the article can be found at the end of the article. METHOD ARTICLE Prediction of cell position using single-cell transcriptomic data: an iterative procedure [version 1; peer review: awaiting peer review] Andrés M. Alonso , Alejandra Carrea , Luis Diambra 1 CREG-CONICET, Universidad Nacional de La Plata, La Plata, Buenos Aires, 1900, Argentina INTech-CONICET, Universidad Nacional de San Martin, Chascomus, Buenos Aires, Argentina 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. To develop new algorithms for this purpose, the Dialogue for Reverse Engineering Assessments and Methods (DREAM) consortium organized a crowd-sourced competition known as DREAM Single Cell Transcriptomics Challenge (SCTC). In the spirit of this framework, we describe here the proposed procedures for adequate reference genes selection, and an iterative procedure to predict spatial expression profile of other genes. Keywords Single-Cell RNA sequencing, Drosophila Embryo, Gene expression Patterns, DREAM Challenge This article is included in the DREAM Challenges gateway. Luis Diambra ( ) Corresponding author: ldiambra@gmail.com : Conceptualization, Formal Analysis, Writing – Original Draft Preparation; : Conceptualization, Formal Author roles: Alonso AM Carrea A Analysis, Writing – Review & Editing; : Conceptualization, Formal Analysis, Supervision, Writing – Original Draft Preparation Diambra L No competing interests were disclosed. Competing interests: The author(s) declared that no grants were involved in supporting this work. Grant information: © 2019 Alonso AM . This is an open access article distributed under the terms of the , which Copyright: et al Creative Commons Attribution License permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Alonso AM, Carrea A and Diambra L. How to cite this article: Prediction of cell position using single-cell transcriptomic data: an iterative F1000Research 2019, :1775 ( ) procedure [version 1; peer review: awaiting peer review] 8 https://doi.org/10.12688/f1000research.20715.1 18 Oct 2019, :1775 ( ) First published: 8 https://doi.org/10.12688/f1000research.20715.1 1,2 1 1 1 2 Reviewer Status AWAITING PEER REVIEW 18 Oct 2019, :1775 ( First published: 8 ) https://doi.org/10.12688/f1000research.20715.1 18 Oct 2019, :1775 ( Latest published: 8 ) https://doi.org/10.12688/f1000research.20715.1 v1 Page 1 of 7 F1000Research 2019, 8:1775 Last updated: 18 OCT 2019