- Abstract:
-
Single-cell RNA sequencing (scRNA-seq) is increasingly used to study gene expression at the level of individual cells. However, preparing raw sequence data for further analysis is not a straightforward process. Biases, artifacts and other sources of unwanted variation are present in the data, requiring substantial time and effort to be spent on pre-processing, quality control (QC) and normalization.We have developed the R/Bioconductor package scater to facilitate rigorous pre-processing, qual...
Expand abstract - Publication status:
- Published
- Peer review status:
- Peer reviewed
- Version:
- Publisher's version
- Files:
-
-
(pdf, 917.9KB)
-
- Publisher copy:
- 10.1093/bioinformatics/btw777
-
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- Publisher:
- Oxford University Press Publisher's website
- Journal:
- Bioinformatics Journal website
- Volume:
- 33
- Issue:
- 8
- Pages:
- 1179-1186
- Publication date:
- 2017-01-14
- Acceptance date:
- 2016-12-07
- DOI:
- EISSN:
-
1367-4811
- ISSN:
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1367-4803
- Pubs id:
-
pubs:673358
- URN:
-
uri:d5c7de0c-3a03-4874-81a5-e555d3ef1282
- UUID:
-
uuid:d5c7de0c-3a03-4874-81a5-e555d3ef1282
- Local pid:
- pubs:673358
- Paper number:
- 8
- Copyright holder:
- McCarthy et al.
- Copyright date:
- 2017
- Notes:
-
© The Author 2017. Published by Oxford University Press.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License.
Journal article
Scater: pre-processing, quality control, normalization and visualization of single-cell RNA-seq data in R
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