Normalization of Single-Cell Data is a computational procedure in single-cell transcriptomics that adjusts gene expression measurements to correct for technical variations such as sequencing depth and library size while preserving biological heterogeneity across individual cells.
253
Publications
53.7K
Citations
1.2K
Authors
447
Institutions
Publications per year
2017–2026
183
Variants
Single-cell Data Normalization
Publications
253
mRNA-Seq whole-transcriptome analysis of a single cell
Fuchou Tang, Cátálin Bárbácioru, Yangzhou Wang et al. · Nature Methods · 2009 · 4K citations
Single-cell mRNA quantification and differential analysis with Census
Xiaojie Qiu, Andrew J. Hill, Jonathan S. Packer et al. · Nature Methods · 2017 · 2.1K citations
1–5 of 253
Authors
1.2K
- JC
11
h-index
- AT
9
h-index
- SA
7
h-index
- DR
7
h-index
- RA
7
h-index
1–5 of 1.2K
Institutions
447
European Bioinformatics Institute
Cambridge, United Kingdom
19 h-index
54 publications
43.2K citations
Wellcome Sanger Institute
Cambridge, United Kingdom
19 h-index
61 publications
34.2K citations
University of Cambridge
Cambridge, United Kingdom
17 h-index
30 publications
21.5K citations
Harvard University
Cambridge, United States
10 h-index
24 publications
8.9K citations
University of California, Berkeley
Berkeley, United States
10 h-index
36 publications
4.6K citations
Cornell University
Ithaca, United States
9 h-index
15 publications
2.5K citations
University of Toronto
Toronto, Canada
8 h-index
23 publications
4K citations
The University of Melbourne
Melbourne, Australia
8 h-index
36 publications
3.9K citations
1–8 of 447
Venues
- Nature Methods
23 publications · 16K citations
22
h-index
- bioRxiv (Cold Spring Harbor Laboratory)
Repository · 37 publications · 1.1K citations
19
h-index
- Genome biology
17 publications · 9.7K citations
17
h-index
- Bioinformatics
15 publications · 3.1K citations
14
h-index
- BMC Bioinformatics
15 publications · 906 citations
13
h-index
1–5