When less is more: sketching with minimizers in genomics

Area of Science:

• Bioinformatics and Computational Biology
• Genomics and Molecular Biology

Background:

• The rapid growth of sequencing data necessitates efficient data processing methods.
• Minimizers offer a way to reduce data volume while preserving essential properties for analysis.

Purpose of the Study:

• To introduce the concept and applications of minimizers in genomic data analysis.
• To review recent advancements and alternative data sketching techniques.

Main Methods:

• Introduction to the minimizer technique.
• Review of methodological developments.
• Survey of applications in genomics.

Main Results:

• Minimizers effectively reduce the scale of genomic datasets.
• Demonstrated utility across various applications like genome assembly and metagenomics.
• Highlighting alternative sketching methods such as syncmers and strobemers.

Conclusions:

• Minimizers and related techniques are crucial for managing large-scale genomic data.
• These methods are indispensable tools in contemporary bioinformatics.
• Continued development of data sketching is vital for future biological insights.