How to fix slow or failing BLAST runs?

Optimize the Query Sequence

• Ensure the input sequence is free from ambiguous characters or errors. Use sequence cleaning tools to remove noise.

 

• Reduce the length of query sequences; break large sequences into smaller fragments to speed up computations.

Adjust BLAST Parameters

• Set an appropriate Expectation value (E-value) to limit the number of statistically significant matches returned.

 

• Modify the word size parameter for nucleotide searches to increase speed by adjusting the sensitivity.

 

• Utilize the task-specific options such as 'blastn-short' for shorter queries which are optimized for such scenarios.

Optimize Database Selection

• Choose the smallest database necessary to achieve your research goals, reducing the number of sequences to process.

 

• Consider downloading and filtering the database locally instead of using a larger public version, which may include many irrelevant entries.

Utilize Computational Resources Efficiently

• If running BLAST locally, ensure that hardware resources like CPU and memory are sufficiently allocated. Consider using a more powerful machine or cloud-based resources.

 

• When using NCBI servers, understand the queue limitations and choose off-peak hours for quicker processing.

 

• Use parallel processing capabilities by splitting the task into smaller chunks that can be run simultaneously.

Check Software and Version

• Ensure the version of BLAST you are using is up-to-date with the latest patches and improvements for performance and bug fixes.

 

• If issues persist, consider using an alternative tool or implementation, such as blat or diamond for specific tasks, to see if performance improves.

Analyze System Logs and Outputs

• Review the BLAST logs to understand bottlenecks or errors that might be occurring during execution.

 

• Look for patterns in failed runs and adjust parameters accordingly, keeping track of any changes that improve performance.