Decosus: An R Framework for Universal Integration of Cell Proportion Estimation Methods.
Journal article
Anene, C.A., Taggart, E., Harwood, C., Pennington, D.J. and Wang, J. (2022). Decosus: An R Framework for Universal Integration of Cell Proportion Estimation Methods. Frontiers in genetics. 13, p. 802838. https://doi.org/10.3389/fgene.2022.802838
Authors | Anene, C.A., Taggart, E., Harwood, C., Pennington, D.J. and Wang, J. |
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Abstract | The assessment of the cellular heterogeneity and abundance in bulk tissue samples is essential for characterising cellular and organismal states. Computational approaches to estimate cellular abundance from bulk RNA-Seq datasets have variable performances, often requiring benchmarking matrices to select the best performing methods for individual studies. However, such benchmarking investigations are difficult to perform and assess in typical applications because of the absence of gold standard/ground-truth cellular measurements. Here we describe Decosus, an R package that integrates seven methods and signatures for deconvoluting cell types from gene expression profiles (GEP). Benchmark analysis on a range of datasets with ground-truth measurements revealed that our integrated estimates consistently exhibited stable performances across datasets than individual methods and signatures. We further applied Decosus to characterise the immune compartment of skin samples in different settings, confirming the well-established Th1 and Th2 polarisation in psoriasis and atopic dermatitis, respectively. Secondly, we revealed immune system-related UV-induced changes in sun-exposed skin. Furthermore, a significant motivation in the design of Decosus is flexibility and the ability for the user to include new gene signatures, algorithms, and integration methods at run time. |
Keywords | Gene Expression; R Package; Cell Deconvolution; Method Integration; Immuno-biology |
Year | 2022 |
Journal | Frontiers in genetics |
Journal citation | 13, p. 802838 |
Publisher | Frontiers Media |
ISSN | 1664-8021 |
Digital Object Identifier (DOI) | https://doi.org/10.3389/fgene.2022.802838 |
Web address (URL) | https://www.frontiersin.org/articles/10.3389/fgene.2022.802838/full |
Funder/Client | Academy of Medical Sciences |
Publication dates | |
Online | 01 Apr 2022 |
01 Jan 2022 | |
Publication process dates | |
Deposited | 16 Jun 2022 |
Accepted author manuscript | License File Access Level Open |
License | CC BY |
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https://openresearch.lsbu.ac.uk/item/8zy9y
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Accepted author manuscript
Anene, C.A., Taggart, E., Harwood, C.A., Pennington, D.J. and Wang, J., 2022.pdf | ||
License: CC BY 4.0 | ||
File access level: Open |
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