PT  - JOURNAL ARTICLE
AU  - Yixuan Qiu
AU  - Jiebiao Wang
AU  - Jing Lei
AU  - Kathryn Roeder
TI  - Identification of cell-type-specific marker genes from co-expression patterns in tissue samples
AID  - 10.1101/2020.11.07.373043
DP  - 2020 Jan 01
TA  - bioRxiv
PG  - 2020.11.07.373043
4099  - http://biorxiv.org/content/early/2020/11/08/2020.11.07.373043.short
4100  - http://biorxiv.org/content/early/2020/11/08/2020.11.07.373043.full
AB  - Motivation Marker genes, defined as genes that are expressed primarily in a single cell type, can be identified from the single cell transcriptome; however, such data are not always available for the many uses of marker genes, such as deconvolution of bulk tissue. Marker genes for a cell type, however, are highly correlated in bulk data, because their expression levels depend primarily on the proportion of that cell type in the samples. Therefore, when many tissue samples are analyzed, it is possible to identify these marker genes from the correlation pattern.Results To capitalize on this pattern, we develop a new algorithm to detect marker genes by combining published information about likely marker genes with bulk transcriptome data in the form of a semi-supervised algorithm. The algorithm then exploits the correlation structure of the bulk data to refine the published marker genes by adding or removing genes from the list.Availability and implementation We implement this method as an R package markerpen, hosted on https://github.com/yixuan/markerpen.Contact roeder{at}andrew.cmu.eduCompeting Interest StatementThe authors have declared no competing interest.