Identification of Human Cell Cycle Phase Markers Based on Single-Cell RNA-Seq Data by Using Machine Learning Methods

Figure 1

Flow chart of the whole analysis process of this study. Single-cell RNA sequencing data acquired through the GEO database includes cells from three different cell cycle phases with the following numbers: 346 G1 phase, 387 G2/M phase, and 334 S phase. Subsequently, sorted feature list from the single-cell atlas is generated through feature selection methods. Each list is partitioned into feature subsets which are fed into the four classification algorithms to retrieve the efficient genes, build effective classifiers, and construct classification rules.