I have a GSE data file in csv file format containing fields such as: ID, adj.P.Val, P.Value, t, B, logFC, Gene.symbol, Gene.title. In which adj.P.Val, P.Value, t, B, logFC fields being numeric. What are the factors I need to consider if I want to cluster the data only on logFC using K-Means clustering algorithm ? And first of all is it feasible to perform clustering on GSE data files ? If yes, what should be the approach ? If not, what different kinds of analysis can be performed on such kind of datasets ?
You have multiple questions:
First of all, here is the description of
GSE files or
Series records are supplied by submitters
A Series record links together a group of related Samples and provides a focal point and description of the whole study. Series records may also contain tables describing extracted data, summary conclusions, or analyses. Each Series record is assigned a unique and stable GEO accession number (GSExxx).
Apparently the authors have provided their (differential expression) analysis results (p-values, adjusted p-values, logFC, ...). And the table you are sharing in your question does not look like a typical GSE profile.
On your question on the feasibility of clustering based on GSE data: that would depend on the features (columns) you are provided with, you should have an understanding of each feature that you have. In your case, you can cluster your genes based on p-value, adjusted p-value and logFC, but would that make sense?
Regarding your question using k-means on only one variable, logFC: This link points to a related discussion. Short answer is "technically yes".
Your last question depends on the "research question" you have, if you are asking about the table in your question: pathway analysis, gene set enrichment analysis, checking for co-expressed modules, ...