Single-cell Sequencing Data Analysis Reveals Heterogeneity of Glioblastoma Multiforme

Abstract

Glioblastoma multiforme is a highly malignant brain tumor. The complex cellular heterogeneity and classification of cell groups have been key factors affecting tumor progression and treatment response. This paper analyzed GBM sequencing data through single-cell RNA sequencing. Firstly, flitering genes and cells according to some specific thresholds. After nomalizing the gene expression matrix, some high-variance genes were selected, and then this paper applied principle component analysis to reduce the dimensions of genes. To identify the cell types, this paper implemented louvain clustering to get 16 clusters, followed by cell annotation. Meanwhile, marker genes were used to find functional pathways and here some conclusions were made about brain cancer research.