Alleviating batch effects in cell type deconvolution with SCCAF-D

Shuo Feng, Liangfeng Huang, Anna Vathrakokoili Pournara, Ziliang Huang, Xinlu Yang, Yongjian Zhang, Alvis Brazma, Ming Shi (), Irene Papatheodorou () and Zhichao Miao ()
Additional contact information
Shuo Feng: Guangzhou Medical University
Liangfeng Huang: Guangzhou Medical University
Anna Vathrakokoili Pournara: Wellcome Genome Campus
Ziliang Huang: Guangzhou Medical University
Xinlu Yang: Harbin Red Cross Central Hospital
Yongjian Zhang: Harbin Medical University the Sixth Affiliated Hospital
Alvis Brazma: Wellcome Genome Campus
Ming Shi: Harbin Institute of Technology
Irene Papatheodorou: Norwich Research Park
Zhichao Miao: Guangzhou Medical University

Nature Communications, 2024, vol. 15, issue 1, 1-14

Abstract: Abstract Cell type deconvolution methods can impute cell proportions from bulk transcriptomics data, revealing changes in disease progression or organ development. But benchmarking studies often use simulated bulk data from the same source as the reference, which limits its application scenarios. This study examines batch effects in deconvolution and introduces SCCAF-D, a computational workflow that ensures a Pearson Correlation Coefficient above 0.75 across simulated and real bulk data for various tissue types. Applied to non-alcoholic fatty liver disease, SCCAF-D unveils meaningful insights into changes in cell proportions during disease progression.

Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.nature.com/articles/s41467-024-55213-x Abstract (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-55213-x

Ordering information: This journal article can be ordered from
https://www.nature.com/ncomms/

DOI: 10.1038/s41467-024-55213-x

Access Statistics for this article

Nature Communications is currently edited by Nathalie Le Bot, Enda Bergin and Fiona Gillespie

More articles in Nature Communications from Nature
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().