If, by validation, you mean characterizing your differentially expressed genes, you can use GSEA, gene ontology term enrichment, pathway analysis, etc.
If I am validating my differential gene expression data for tumor versus normal, I might use one of those tools to see if the expected cancer pathways are represented among my differentially expressed genes.
If I'm analyzing a high-throughput genome-wide loss-of-function genetic screen, I might use one of those tools to validate whether known essential genes are represented among my hits.
It's basically using known annotated gene sets / pathways to serve as a positive control for analyzing your experiments.
If, by validation, you mean characterizing your differentially expressed genes, you can use GSEA, gene ontology term enrichment, pathway analysis, etc.
If I am validating my differential gene expression data for tumor versus normal, I might use one of those tools to see if the expected cancer pathways are represented among my differentially expressed genes.
If I'm analyzing a high-throughput genome-wide loss-of-function genetic screen, I might use one of those tools to validate whether known essential genes are represented among my hits.
It's basically using known annotated gene sets / pathways to serve as a positive control for analyzing your experiments.