Evaluation of Methods in Removing Batch Effects on RNA-seq Data
It is common and advantageous for researchers to combine RNA-seq data from similar studies to increase statistical power in genomics analysis. However the unwanted noise and hidden artifacts such as batch effects could dramatically reduce the accuracy of statistical inference. The performance of thr...
Main Authors: | Qian Liu, Marianthi Markatou |
---|---|
Format: | Article |
Language: | English |
Published: |
International Biological and Medical Journals Publishing House Co., Limited
2016-04-01
|
Series: | Infectious Diseases and Translational Medicine |
Subjects: | |
Online Access: | http://www.tran-med.com/EN/abstract/abstract24.shtml |
Similar Items
-
A benchmark of batch-effect correction methods for single-cell RNA sequencing data
by: Hoa Thi Nhu Tran, et al.
Published: (2020-01-01) -
Comparison of RNA isolation methods on RNA-Seq: implications for differential expression and meta-analyses
by: Amanda N. Scholes, et al.
Published: (2020-03-01) -
A comparison of methods accounting for batch effects in differential expression analysis of UMI count based single cell RNA sequencing
by: Wenan Chen, et al.
Published: (2020-01-01) -
BERMUDA: a novel deep transfer learning method for single-cell RNA sequencing batch correction reveals hidden high-resolution cellular subtypes
by: Tongxin Wang, et al.
Published: (2019-08-01) -
Correction of batch effects in single cell RNA sequencing data using ComBat-Seq
by: Dullea, Jonathan Tyler
Published: (2021)