FreePSI: an alignment-free approach to estimating exon-inclusion ratios without a reference transcriptome.

Area of Science:

• Genomics
• Molecular Biology
• Bioinformatics

Background:

• Alternative splicing is crucial for eukaryotic cellular processes.
• Exon-inclusion ratio (percent spliced in) is a key measure of alternative splicing.
• Current genome-wide methods require a reference transcriptome.

Purpose of the Study:

• To develop an alignment-free method for genome-wide exon-inclusion ratio estimation.
• To enable alternative splicing analysis without a reference transcriptome.

Main Methods:

• Proposed FreePSI, an alignment-free method utilizing a probabilistic generative model based on k-mer profiles.
• Employed an efficient expectation-maximization algorithm with a divide-and-conquer strategy and conjugate gradient projection descent.
• Quantified exon-inclusion ratios at the genome scale.

Main Results:

• FreePSI demonstrated comparable accuracy and efficiency to existing methods on simulated and real RNA-Seq data.
• The method performs well even without a reference transcriptome.
• Validated the utility of FreePSI for alternative splicing analysis.

Conclusions:

• FreePSI provides a valuable tool for alternative splicing analysis, particularly for organisms with limited or no reference transcriptome.
• The alignment-free approach enhances accessibility and applicability in genomics research.
• FreePSI is freely available, promoting wider adoption in the scientific community.