{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,7]],"date-time":"2026-03-07T03:55:44Z","timestamp":1772855744562,"version":"3.50.1"},"reference-count":47,"publisher":"Oxford University Press (OUP)","issue":"3","license":[{"start":{"date-parts":[[2025,6,28]],"date-time":"2025-06-28T00:00:00Z","timestamp":1751068800000},"content-version":"vor","delay-in-days":58,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"name":"Foundation of Key Laboratory of System Control and Information Processing, Ministry of Education, China","award":["Scip20240104"],"award-info":[{"award-number":["Scip20240104"]}]},{"name":"Natural Science Foundation of Fujian Province of China","award":["2022J05012"],"award-info":[{"award-number":["2022J05012"]}]},{"DOI":"10.13039\/501100018537","name":"National Science and Technology Major Project","doi-asserted-by":"publisher","award":["2021ZD0112600"],"award-info":[{"award-number":["2021ZD0112600"]}],"id":[{"id":"10.13039\/501100018537","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,5,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Single-cell RNA-seq facilitates the understanding of cell types and states and the revealing of the cellular heterogeneity in developmental processes and disease mechanisms. However, the dropout events in single-cell RNA-seq data, in which genes are not detected due to technical noise or limited sequencing depth, seriously affect downstream analyses. Imputation is an effective way to relieve the impact of dropout events. However, the current methods may introduce new noise or modify the high expression values in the imputation process and their performance may be lower than expected when dealing with data with a high dropout rate, facing with different types of data, and aiming at various downstream analyses. We propose a two-stage imputation algorithm, scTsI, for single-cell RNA-seq data. In the first stage, scTsI imputes the zero values using the information of neighboring cells and genes. In the second stage, scTsI transforms the expression matrix into a vector, performs row transformation, and adjusts the imputed values through ridge regression and leveraging bulk RNA-seq data as a constraint. scTsI ensures that the original highly expressed values are unchanged, avoids introducing new noise, and allows sparse matrix input to accelerate imputation. We conduct experiments on a variety of simulated and real data with different dropout rates and compare scTsI with the commonly used imputation methods. The results show that scTsI can restore gene expression and maintain cell\u2013cell similarity across different data dimensions and dropout rates. scTsI can also improve the performance of data visualization, clustering, and cell trajectory inference.<\/jats:p>","DOI":"10.1093\/bib\/bbaf298","type":"journal-article","created":{"date-parts":[[2025,6,28]],"date-time":"2025-06-28T04:12:51Z","timestamp":1751083971000},"source":"Crossref","is-referenced-by-count":3,"title":["scTsI: an effective two-stage imputation method for single-cell RNA-seq data"],"prefix":"10.1093","volume":"26","author":[{"given":"Hongyu","family":"Zhang","sequence":"first","affiliation":[{"name":"Department of Automation, Xiamen University , Xiang'an South Road, Xiang'an District, Xiamen, Fujian 361102 ,","place":["China"]}]},{"given":"Weining","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Automation, Xiamen University , Xiang'an South Road, Xiang'an District, Xiamen, Fujian 361102 ,","place":["China"]}]},{"given":"Jinting","family":"Guan","sequence":"additional","affiliation":[{"name":"Key Laboratory of System Control and Information Processing, Ministry of Education , Dongchuan Road, Minhang District, Shanghai , Shanghai 200240,","place":["China"]},{"name":"National Institute for Data Science in Health and Medicine, Xiamen University , Xiang'an South Road, Xiang'an District, Xiamen, Fujian 361102 ,","place":["China"]}]}],"member":"286","published-online":{"date-parts":[[2025,6,28]]},"reference":[{"key":"2025062800124455300_ref1","doi-asserted-by":"crossref","first-page":"3730","DOI":"10.1080\/07391102.2019.1659859","article-title":"Single-cell RNA-Seq: A next generation sequencing tool for a high-resolution view of the individual cell","volume":"38","author":"Stevenson","year":"2020","journal-title":"J Biomol Struct Dyn"},{"key":"2025062800124455300_ref2","doi-asserted-by":"crossref","first-page":"618","DOI":"10.1038\/nrg3542","article-title":"Single-cell 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