Theoretical prediction of assembly contiguity

Z-value predicts mean contig length from read length, coverage, and genome properties for a simple single-k assembler on error-free data, matching 14-genome benchmarks within <2% mean absolute error.

• Why it matters: Modern sequencing needs design rules for how deeply to sequence to achieve long-enough contigs, but classic Lander–Waterman theory doesn’t fit current high-throughput data.
• What they did: The authors derive a Z-value formula using read length, coverage, and genome properties, validate it on 14 genomes, and use it to select k, coverage, and even compare instruments under budget tradeoffs.
• The result: Z-value is highly accurate (mean absolute prediction error <2%) and extends to predicting Velvet performance and guiding coverage–read-length instrument choices when resources are limited.

AI summary of the abstract · may contain errors · not medical advice · read the paper.