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Transcriptomics

Improved RNA-seq normalization

Nature Genetics volume 54, page 1584 (2022)Cite this article

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RNA sequencing (RNA-seq) is a widely used method for transcriptome profiling, but is prone to technical and biological confounding factors such as sequencing library size, batch effects and tumor purity in cancer samples. Molania et al. present an improved method to correct for these sources of unwanted variation based on their ‘removing unwanted variation III’ (RUV-III) approach known as pseudo-replicates of pseudo-samples (PRPS). As RUV-III requires technical replicates, PRPS surmounts this issue via an in silico analysis of relatively homogeneous samples that can then be used to normalize the full dataset. Applied to around 11,000 samples analyzed by The Cancer Genome Atlas (TCGA), the authors found that this improved normalization method affects downstream gene co-expression and survival analyses in a range of tumor entities. These results highlight that correcting for unwanted variation is a vital, albeit difficult, step in the processing of transcriptomic data, and researchers who routinely re-use data generated by large-scale genomics projects such as TCGA should be aware of technical developments that may affect the conclusions drawn from their analyses.

Original reference: Nat. Biotech. https://doi.org/10.1038/s41587-022-01440-w (2022)

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  1. Nature Genetics https://www.nature.com/ng

    Michael Fletcher

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  1. Michael Fletcher
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Correspondence to Michael Fletcher.

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Fletcher, M. Improved RNA-seq normalization. Nat Genet 54, 1584 (2022). https://doi.org/10.1038/s41588-022-01217-6

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