New methods to analyse microarray data that partially lack a reference signal.

Area of Science:

• Microbiology
• Genomics
• Bioinformatics

Background:

• Microarray-based Comparative Genomic Hybridisation (CGH) is vital for bacterial strain comparison.
• Interpreting CGH data requires a reliable reference for signal intensity comparison.
• Pan-genome microarrays pose challenges for reference DNA production, hindering analysis of accessory genes.

Purpose of the Study:

• To develop novel methods for determining gene presence and divergence in Staphylococcus aureus multistrain PCR product microarray-based CGH.
• To address the challenge of missing reference DNA for certain probes in CGH analysis.

Main Methods:

• Developed six new methods to predict gene divergence and presence on a multistrain Staphylococcus aureus DNA microarray.
• Evaluated methods based on specificity and positive predictive value (PPV), considering signal intensity relative to background and reference signals.

Main Results:

• Method 4, defining gene presence by a signal at least twice the background and higher than the reference, demonstrated superior test characteristics.
• Method 4 achieved 100% specificity and 82% PPV when compared to sequence data for all spots.
• This method allowed analysis of an additional 6-17% of genes not present in the reference strain.

Conclusions:

• A definition of gene presence based on signal intensity (at least twice background and higher than reference) is recommended for CGH analysis.
• Method 4 significantly enhances the analysis of microarray data with partially missing reference signals.
• This approach improves the comprehensive assessment of genomic variability in bacterial populations.