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Related Experiment Video

Updated: May 21, 2026

Highly Multiplexed, Super-resolution Imaging of T Cells Using madSTORM

Highly Multiplexed, Super-resolution Imaging of T Cells Using madSTORM

Published on: June 24, 2017

New finite-size correction for local alignment score distributions.

Yonil Park¹, Sergey Sheetlin, Ning Ma

¹National Center for Biotechnology Information, National Library of Medicine, Bethesda, MD 20894, USA.

BMC Research Notes

|June 14, 2012

Summary

A new finite-size correction improves local alignment probability calculations by considering sequence length distributions. This enhances sensitivity, particularly for shorter sequences, and is now integrated into BLAST+ and NCBI BLAST.

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Area of Science:

Bioinformatics
Computational Biology
Sequence Analysis

Background:

Local alignment algorithms assess match significance by calculating probabilities.
Accurate probability calculation may require finite-size corrections for sequence lengths.
Alignments near sequence ends can be affected by limited sequence availability.

Purpose of the Study:

To develop an improved finite-size correction method for local alignment probability calculations.
To enhance the sensitivity and accuracy of statistical significance assessment in sequence alignments.
To address limitations in current methods, especially for shorter sequences.

Main Methods:

Developed a novel finite-size correction considering the distribution of sequence lengths.
Utilized a test set derived from the ASTRAL database for evaluation.
Assessed performance using Receiver Operating Characteristic (ROC) scores.

Main Results:

The improved correction enhances sensitivity and avoids underestimation of significance for short sequences.
Demonstrated improved ROC scores, particularly for shorter sequences, compared to existing methods.
The new method provides a more accurate assessment of local alignment probabilities.

Conclusions:

The refined finite-size correction significantly improves local alignment probability calculations.
This advancement enhances the reliability of statistical significance assessment in sequence analysis.
The improved method is now implemented in the widely used BLAST+ package and the NCBI BLAST web service.