SCMarker: Ab initio marker selection for single cell transcriptome profiling
Single-cell RNA-sequencing data generated by a variety of technologies, such as Drop-seq and SMART-seq, can reveal simultaneously the mRNA transcript levels of thousands of genes in thousands of cells. It is often important to identify informative genes or cell-type-discriminative markers to reduce...
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Published in: | PLoS computational biology 2019-10, Vol.15 (10), p.e1007445 |
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description | Single-cell RNA-sequencing data generated by a variety of technologies, such as Drop-seq and SMART-seq, can reveal simultaneously the mRNA transcript levels of thousands of genes in thousands of cells. It is often important to identify informative genes or cell-type-discriminative markers to reduce dimensionality and achieve informative cell typing results. We present an ab initio method that performs unsupervised marker selection by identifying genes that have subpopulation-discriminative expression levels and are co- or mutually-exclusively expressed with other genes. Consistent improvements in cell-type classification and biologically meaningful marker selection are achieved by applying SCMarker on various datasets in multiple tissue types, followed by a variety of clustering algorithms. The source code of SCMarker is publicly available at https://github.com/KChen-lab/SCMarker. |
doi_str_mv | 10.1371/journal.pcbi.1007445 |
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subjects | Algorithms B cells Base Sequence - genetics Bioinformatics Biology Biology and Life Sciences Biomarkers Cancer Cluster Analysis Clustering Computational Biology - methods Datasets Gene expression Gene Expression Profiling - methods Gene sequencing Genes Genetic research Genomes Head & neck cancer Humans Medicine and Health Sciences Messenger RNA Metastasis Principal components analysis Research and analysis methods RNA RNA - genetics Sequence Analysis, RNA - methods Single-Cell Analysis - methods Software Source code Technology Transcription Transcriptome - genetics |
title | SCMarker: Ab initio marker selection for single cell transcriptome profiling |
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