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2DImpute: imputation in single-cell RNA-seq data from correlations in two dimensions.

ABSTRACT: SUMMARY:We developed 2DImpute, an imputation method for correcting false zeros (known as dropouts) in single-cell RNA-sequencing (scRNA-seq) data. It features preventing excessive correction by predicting the false zeros and imputing their values by making use of the interrelationships between both genes and cells in the expression matrix. We showed that 2DImpute outperforms several leading imputation methods by applying it on datasets from various scRNA-seq protocols. AVAILABILITY AND IMPLEMENTATION:The R package of 2DImpute is freely available at GitHub (https://github.com/zky0708/2DImpute). CONTACT:d.anastassiou@columbia.edu. SUPPLEMENTARY INFORMATION:Supplementary data are available at Bioinformatics online.

SUBMITTER: Zhu K

PROVIDER: S-EPMC7267828 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

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2DImpute: imputation in single-cell RNA-seq data from correlations in two dimensions.

Zhu Kaiyi K Anastassiou Dimitris D

Bioinformatics (Oxford, England) 20200601 11

<h4>Summary</h4>We developed 2DImpute, an imputation method for correcting false zeros (known as dropouts) in single-cell RNA-sequencing (scRNA-seq) data. It features preventing excessive correction by predicting the false zeros and imputing their values by making use of the interrelationships between both genes and cells in the expression matrix. We showed that 2DImpute outperforms several leading imputation methods by applying it on datasets from various scRNA-seq protocols.<h4>Availability an ...[more]

PMID: 32108864

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