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pmid:34316700
On the impact of batch effect correction in TCGA isomiR expression data.
Susanne Ibing · Birgitta E Michels · Moritz Mosdzien · Helen R Meyer · Lars Feuerbach · Cindy Körner
NAR cancer · 2021 doi:10.1093/narcan/zcab007
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Complete file
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The Cancer Genome Atlas (TCGA) provides isomiR-level expression data for patients of various cancer entities collected in a multi-center approach over several years. However, the impact of batch effects within individual cohorts has not been systematically investigated and corrected for before. Therefore, the aim of this study was to identify relevant cohort-specific batch variables and generate batch-corrected isomiR expression data for 16 TCGA cohorts. The main batch variables included sequencing platform, plate, sample purity and sequencing depth. Platform bias was related to certain length and sequence features of individual recurrently affected isomiRs. Furthermore, significant downregulation of reported tumor suppressive isomiRs in lung tumor tissue compared to normal samples was only observed after batch correction, highlighting the importance of working with corrected data. Batch-corrected datasets for all cohorts including quality control are provided as supplement. 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