DWLS: Gene Expression Deconvolution Using Dampened Weighted Least Squares
Dampened weighted least squares (DWLS) is an estimation method for gene expression deconvolution, in which the cell-type composition of a bulk RNA-seq data set is computationally inferred. This method corrects common biases towards cell types that are characterized by highly expressed genes and/or are highly prevalent, to provide accurate detection across diverse cell types. To begin, the user must input a bulk RNA-seq data set, along with a labeled representative single-cell RNA-seq data set that will serve to generate cell-type-specific gene expression profiles. Ideally, the single-cell data set will contain cells from all cell types that may be found in the bulk data. DWLS will return the cell-type composition of the bulk data.
Data Sources
[1] Schelker M, Feau S, Du J, Ranu N, Klipp E, MacBeath G, Schoeberl B, Raue A: Estimation of immune cell content in tumour tissue using single-cell RNA-seq data. Nat Commun 2017, 8:2032.
[2] Yan KS, Janda CY, Chang J, Zheng GXY, Larkin KA, Luca VC, Chia LA, Mah AT, Han A, Terry JM, et al: Non-equivalence of Wnt and R-spondin ligands during Lgr5. Nature 2017, 545:238-242.
[3] Han X, Wang R, Zhou Y, Fei L, Sun H, Lai S, Saadatpour A, Zhou Z, Chen H, Ye F, et al: Mapping the Mouse Cell Atlas by Microwell-Seq. Cell 2018, 172:1091-1107.e1017.
References
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