{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,26]],"date-time":"2026-02-26T20:34:16Z","timestamp":1772138056359,"version":"3.50.1"},"reference-count":61,"publisher":"Oxford University Press (OUP)","issue":"21","license":[{"start":{"date-parts":[[2022,9,5]],"date-time":"2022-09-05T00:00:00Z","timestamp":1662336000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Japan Society for the Promotion of Science (JSPS) KAKENHI","award":["20K19915"],"award-info":[{"award-number":["20K19915"]}]},{"name":"Japan Society for the Promotion of Science (JSPS) KAKENHI","award":["17H06300"],"award-info":[{"award-number":["17H06300"]}]},{"name":"Japan Society for the Promotion of Science (JSPS) KAKENHI","award":["21H03124"],"award-info":[{"award-number":["21H03124"]}]},{"name":"Japan Society for the Promotion of Science (JSPS) KAKENHI","award":["19H03696"],"award-info":[{"award-number":["19H03696"]}]},{"name":"Japan Society for the Promotion of Science (JSPS) KAKENHI","award":["19K20394"],"award-info":[{"award-number":["19K20394"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,10,31]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Motivation<\/jats:title>\n                    <jats:p>Cell\u2013cell communications regulate internal cellular states, e.g. gene expression and cell functions, and play pivotal roles in normal development and disease states. Furthermore, single-cell RNA sequencing methods have revealed cell-to-cell expression variability of highly variable genes (HVGs), which is also crucial. Nevertheless, the regulation of cell-to-cell expression variability of HVGs via cell\u2013cell communications is still largely unexplored. The recent advent of spatial transcriptome methods has linked gene expression profiles to the spatial context of single cells, which has provided opportunities to reveal those regulations. The existing computational methods extract genes with expression levels influenced by neighboring cell types. However, limitations remain in the quantitativeness and interpretability: they neither focus on HVGs nor consider the effects of multiple neighboring cell types.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Here, we propose CCPLS (Cell\u2013Cell communications analysis by Partial Least Square regression modeling), which is a statistical framework for identifying cell\u2013cell communications as the effects of multiple neighboring cell types on cell-to-cell expression variability of HVGs, based on the spatial transcriptome data. For each cell type, CCPLS performs PLS regression modeling and reports coefficients as the quantitative index of the cell\u2013cell communications. Evaluation using simulated data showed our method accurately estimated the effects of multiple neighboring cell types on HVGs. Furthermore, applications to the two real datasets demonstrate that CCPLS can extract biologically interpretable insights from the inferred cell\u2013cell communications.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Availability and implementation<\/jats:title>\n                    <jats:p>The R package is available at https:\/\/github.com\/bioinfo-tsukuba\/CCPLS. The data are available at https:\/\/github.com\/bioinfo-tsukuba\/CCPLS_paper.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Supplementary information<\/jats:title>\n                    <jats:p>Supplementary data are available at Bioinformatics online.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btac599","type":"journal-article","created":{"date-parts":[[2022,9,4]],"date-time":"2022-09-04T07:57:36Z","timestamp":1662278256000},"page":"4868-4877","source":"Crossref","is-referenced-by-count":8,"title":["CCPLS reveals cell-type-specific spatial dependence of transcriptomes in single cells"],"prefix":"10.1093","volume":"38","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7540-5115","authenticated-orcid":false,"given":"Takaho","family":"Tsuchiya","sequence":"first","affiliation":[{"name":"Bioinformatics Laboratory, Faculty of Medicine, University of Tsukuba , Tsukuba, Ibaraki 305-8577, Japan"},{"name":"Center for Artificial Intelligence Research, University of Tsukuba , Tsukuba, Ibaraki 305-8577, Japan"}]},{"given":"Hiroki","family":"Hori","sequence":"additional","affiliation":[{"name":"Bioinformatics Laboratory, Faculty of Medicine, University of Tsukuba , Tsukuba, Ibaraki 305-8577, Japan"},{"name":"Doctoral Program in Medical Sciences, Graduate School of Comprehensive Human Sciences, University of Tsukuba , Tsukuba, Ibaraki 305-8577, Japan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1606-2762","authenticated-orcid":false,"given":"Haruka","family":"Ozaki","sequence":"additional","affiliation":[{"name":"Bioinformatics Laboratory, Faculty of Medicine, University of Tsukuba , Tsukuba, Ibaraki 305-8577, Japan"},{"name":"Center for Artificial Intelligence Research, University of Tsukuba , Tsukuba, Ibaraki 305-8577, Japan"}]}],"member":"286","published-online":{"date-parts":[[2022,9,5]]},"reference":[{"key":"2023021713091862700_","doi-asserted-by":"crossref","first-page":"97","DOI":"10.1002\/wics.51","article-title":"Partial least squares regression and projection on latent structure regression (PLS regression)","volume":"2","author":"Abdi","year":"2010","journal-title":"WIREs Comp. 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