Human gene data forms two main groups across clustering methods
Clustering of High-Dimensional Human Gene Score Data for Target Cell Classification
Machine Learning
Summary
Scientists looked at large sets of human gene activity scores to see if they could group cells into similar types. They tested both complete gene data and a smaller subset of important genes, using different ways to handle missing information. After analyzing the data with common clustering methods, they found that cells consistently grouped into two main clusters. This suggests a stable way to classify cells based on gene activity patterns.
What this means in practice
- •For bioinformatics engineers: Design cell classification tools that use stable gene expression clusters identified across datasets and clustering methods.
- •For pharmaceutical development teams: Use robust clustering of kinase gene data to help classify target cell types for drug development.
Authors
S. Das, V. Madala, P. Majumder, N. S. Sinha
Abstract
The goal is to investigate whether the total human gene-score dataset and the selected human kinase-gene dataset exhibit the same number of clusters when analysed using the same set of 769 features. Two datasets were considered: the complete gene score dataset and a subset containing selected kinase genes. Two missing-data strategies were investigated. In Case I, rows containing missing gene-score values were removed. In Case II, rows with more than 20% missing values were excluded and the other missing values were replaced by the corresponding column mean. For each case, the data were scaled and principal component analysis (PCA) was performed before clustering. Four clustering approaches were considered: K-Means, Hierarchical Clustering, Fuzzy C-Means, and Graph-based Clustering. Across both datasets and both missing-data treatments, the optimal number of clusters was found to be two. In the absence of an optimal number of clusters, the quality of clustering was assessed using the Silhouette score. Relatively high Silhouette scores were obtained in all cases.