Transcriptome is a powerful tool for the study of functional genes, and a large number of differential genes and regulatory networks can be obtained by transcriptome sequencing, but it is difficult to determine the key pathways. The metabolome is the direct embodiment of phenotype, and the use of metabolomics data can reflect phenotypic changes, but it cannot explain the genetic mechanism that affects phenotype. Using transcriptome + metabolome multi-omics analysis, organisms can be studied at different levels, and the data of different omics also play a role in mutual validation, so as to comprehensively and systematically resolve complex biological processes.

The transcriptome can be analyzed by standard analysis procedures to obtain the analysis results of differentially expressed genes, and the results of differential metabolites and metabolic pathways can be obtained by metabolomics. By conducting joint analysis of differential genes and differential metabolites, calculating the correlation between differential genes and differential metabolites, and constructing a correlation network, the key genes that cause changes in metabolites can be identified and the key regulatory pathways can be determined. The conventional joint analysis mainly includes correlation analysis, KEGG pathway analysis, KEGG enrichment analysis, etc.

Joint analytics benefits

l Through the analysis of expression levels at different levels, it can make up for the lack of single omics data and noise interference;

l At the same time, biological problems can be explored from the two directions of "cause" and "effect", and the mutual verification effect is more obvious, so as to avoid false positives;

l Explain the correlation mechanism between molecular regulation and phenotype, and systematically and comprehensively analyze the function and regulatory mechanism of biomolecules;

l Remove the false from the massive data and keep the true, and screen out the key metabolic pathways, genes and metabolites for follow-up in-depth experimental analysis and application.