How to refine splice site detection in HISAT2?

Understand HISAT2 Basics

• HISAT2 is a widely-used software for aligning RNA-seq reads to a genome.
• It uses graph-based alignment to quickly and accurately find splice junctions.

Prepare Your Reference Genome and Annotations

• Download the reference genome and the corresponding GTF file with known gene annotations.
• Ensure that the genome is indexed using HISAT2’s indexing tools for efficient processing.

Customize Splice Site Detection

• Use the `--known-splicesite-infile` option to provide a file with known splice sites. This option can be critical for improving splice junction accuracy by providing HISAT2 with a list of known junctions from a trusted source.
• Generate the splice site file from your GTF annotations using the `hisat2_extract_splice_sites.py` script.

Adjust Alignment Sensitivity

• Modify the read alignment parameters to refine the sensitivity. Use `--min-intronlen` and `--max-intronlen` to allow alignment over potential intron sizes expected in your data type.
• Experiment with `--dta` (downstream transcriptome assembly) which is particularly useful for transcriptome analysis as it tries to identify more alignments through splice junctions.

Optimize Computational Resources

• Use multi-threading with the `-p` option to speed up the process and potentially improve the overall detection efficiency.
• Ensure that the computational environment has enough memory allocated for operations dealing with large datasets.

Validate Splice Sites

• After alignment, validate the detected splice sites using benchmarking tools like GffCompare or by comparing against known junctions.
• Consider using visualization tools such as IGV to inspect read alignments and ensure the accuracy of detected splice junctions.

Iterate and Refine

• Review results and make necessary parameter adjustments, especially if the initial results don't align well with expected outcomes.
• Iterate through different alignment strategies and parameter sets to fine-tune the splice site detection based on specific experimental needs.