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Genome Biol ; 25(1): 136, 2024 05 23.
Artigo em Inglês | MEDLINE | ID: mdl-38783325

RESUMO

In droplet-based single-cell and single-nucleus RNA-seq assays, systematic contamination of ambient RNA molecules biases the quantification of gene expression levels. Existing methods correct the contamination for all genes globally. However, there lacks specific evaluation of correction efficacy for varying contamination levels. Here, we show that DecontX and CellBender under-correct highly contaminating genes, while SoupX and scAR over-correct lowly/non-contaminating genes. Here, we develop scCDC as the first method to detect the contamination-causing genes and only correct expression levels of these genes, some of which are cell-type markers. Compared with existing decontamination methods, scCDC excels in decontaminating highly contaminating genes while avoiding over-correction of other genes.


Assuntos
RNA-Seq , Análise de Célula Única , Análise de Célula Única/métodos , RNA-Seq/métodos , Humanos , Biologia Computacional/métodos , Análise de Sequência de RNA/métodos , Núcleo Celular/genética , Software , Animais
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