Cargando…
2DImpute: imputation in single-cell RNA-seq data from correlations in two dimensions
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...
Autores principales: | , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7267828/ https://www.ncbi.nlm.nih.gov/pubmed/32108864 http://dx.doi.org/10.1093/bioinformatics/btaa148 |
_version_ | 1783541485501677568 |
---|---|
author | Zhu, Kaiyi Anastassiou, Dimitris |
author_facet | Zhu, Kaiyi Anastassiou, Dimitris |
author_sort | Zhu, Kaiyi |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-7267828 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-72678282020-06-09 2DImpute: imputation in single-cell RNA-seq data from correlations in two dimensions Zhu, Kaiyi Anastassiou, Dimitris Bioinformatics Applications Notes 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. Oxford University Press 2020-06 2020-02-28 /pmc/articles/PMC7267828/ /pubmed/32108864 http://dx.doi.org/10.1093/bioinformatics/btaa148 Text en © The Author(s) 2020. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Applications Notes Zhu, Kaiyi Anastassiou, Dimitris 2DImpute: imputation in single-cell RNA-seq data from correlations in two dimensions |
title | 2DImpute: imputation in single-cell RNA-seq data from correlations in two dimensions |
title_full | 2DImpute: imputation in single-cell RNA-seq data from correlations in two dimensions |
title_fullStr | 2DImpute: imputation in single-cell RNA-seq data from correlations in two dimensions |
title_full_unstemmed | 2DImpute: imputation in single-cell RNA-seq data from correlations in two dimensions |
title_short | 2DImpute: imputation in single-cell RNA-seq data from correlations in two dimensions |
title_sort | 2dimpute: imputation in single-cell rna-seq data from correlations in two dimensions |
topic | Applications Notes |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7267828/ https://www.ncbi.nlm.nih.gov/pubmed/32108864 http://dx.doi.org/10.1093/bioinformatics/btaa148 |
work_keys_str_mv | AT zhukaiyi 2dimputeimputationinsinglecellrnaseqdatafromcorrelationsintwodimensions AT anastassioudimitris 2dimputeimputationinsinglecellrnaseqdatafromcorrelationsintwodimensions |