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DTD: An R Package for Digital Tissue Deconvolution.

ABSTRACT: Digital tissue deconvolution (DTD) estimates the cellular composition of a tissue from its bulk gene-expression profile. For this, DTD approximates the bulk as a mixture of cell-specific expression profiles. Different tissues have different cellular compositions, with cells in different activation states, and embedded in different environments. Consequently, DTD can profit from tailoring the deconvolution model to a specific tissue context.

SUBMITTER: Schon M

PROVIDER: S-EPMC7074920 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature

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DTD: An R Package for Digital Tissue Deconvolution.

Schön Marian M Simeth Jakob J Heinrich Paul P Görtler Franziska F Solbrig Stefan S Wettig Tilo T Oefner Peter J PJ Altenbuchinger Michael M Spang Rainer R

Journal of computational biology : a journal of computational molecular cell biology 20200129 3

<b>Digital tissue deconvolution (DTD) estimates the cellular composition of a tissue from its bulk gene-expression profile. For this, DTD approximates the bulk as a mixture of cell-specific expression profiles. Different tissues have different cellular compositions, with cells in different activation states, and embedded in different environments. Consequently, DTD can profit from tailoring the deconvolution model to a specific tissue context.</b> <b>Loss-function learning adapts DTD to a specif ...[more]

PMID: 31995409

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