Systems and methods for microarray data analysis

摘要

Clustering is routinely applied in the exploratory analysis of microarray data. Missing entries arise from blemishes on the microarrays. The present invention provides a new method, and computer program and/or computer product thereof to impute missing values. The method involves the steps of clustering microarray data by partitioning the data into a select number of clusters, wherein each data point is iteratively moved from one cluster to another, until two consecutive iterations have resulted in the same partition pattern; obtaining a select number of estimates of the data in the clusters by probabilistic interference; and averaging the select number of estimates to obtain missing values in the microarray data. The method is superior to other imputation models as measured by root mean squared errors.