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Challenges and perspectives in computational deconvolution of genomics data - Nature Methods

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Challenges and perspectives in computational deconvolution of genomics data - Nature Methods

Deciphering cell-type heterogeneity is crucial for systematically understanding tissue homeostasis and its dysregulation in diseases. Computational deconvolution is an efficient approach for estimating cell-type abundances from a variety of omics data. Despite substantial methodological progress in computational deconvolution in recent years, challenges are still outstanding.

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Challenges and perspectives in computational deconvolution of genomics data - Nature Methods

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Challenges and perspectives in computational deconvolution of genomics data - Nature Methods

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