Anomaly detection in mixed high dimensional molecular data

URN to cite this document:: urn:nbn:de:bvb:355-epub-545959
DOI to cite this document:: 10.5283/epub.54595

Buck, Lena ; Schmidt, Tobias ; Feist, Maren ; Schwarzfischer, Philipp ; Kube, Dieter ; Oefner, Peter J.

; Zacharias, Helena U. ; Altenbuchinger, Michael ; Dettmer, Katja

; Gronwald, Wolfram

; Spang, Rainer

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Date of publication of this fulltext: 24 Aug 2023 07:14

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Abstract

Motivation Mixed molecular data combines continuous and categorical features of the same samples, such as OMICS profiles with genotypes, diagnoses, or patient sex. Like all high dimensional molecular data it is prone to incorrect values that can stem from various sources as for example the technical limitations of the measurement devices, errors in the sample preparation or contamination. Most ...