Why Are Genes Not Displayed on the Network Graph When Analyzed with STRING
STRING is a commonly used protein-protein interaction (PPI) database that allows users to generate PPI networks by inputting a set of protein or gene names. If the genes you entered do not appear on the network graph, there could be several reasons:
1. Gene Name Not Recognized or Mismatched
The gene names you entered may be misspelled or use incorrect naming conventions, preventing STRING from recognizing them.
2. Missing PPI Data for Genes
While STRING contains a vast amount of PPI data, not all genes have known PPI information or are included in the database. Therefore, if a gene’s PPI data is missing from the database, it won’t be displayed on the network graph.
3. Display Settings Issues
STRING allows users to adjust parameters such as confidence thresholds when generating network graphs. If these parameters are set too high, some genes may not appear due to insufficient PPI confidence.
4. Network Graph Density
Importing a large number of genes can result in a very dense network graph, making it difficult to recognize and display the nodes and edges clearly.
5. Database Query Limitations
STRING may have query limitations, especially in the free version, which may restrict the number of genes or the size of data per query. This could cause only partial results to be displayed for a large set of genes.
6. Data Filtering
STRING may apply filtering to the input genes, retaining only those that demonstrate strong functional associations with others or possess interaction scores above a specified confidence threshold. Consequently, some genes may be excluded from the final interaction network.
To resolve these issues, you can try the following solutions:
1. Check and confirm that the gene names you entered are correct and that the naming conventions match those in the STRING database. If mismatches occur, try using aliases or standardized gene names.
2. Verify whether you’ve exceeded STRING’s query limits. If so, try querying in batches.
3. Lower the confidence threshold or adjust other parameter settings during analysis to display more genes. If possible, you can also try using other PPI databases for analysis.
4. Finally, consider using other gene network analysis tools or databases to better visualize and analyze the relationships of a large set of genes.
MtoZ Biolabs, an integrated chromatography and mass spectrometry (MS) services provider.
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