Theoretical prediction of assembly contiguity
- 1The Pennsylvania State University
Abstract
Theoretical methods for predicting the performance of assembly algorithms have the potential to guide experimental design on a scale that simulations cannot. A fundamental question of experimental design is how deep to sequence in order to obtain an assembly with long-enough contigs. More precisely, given a certain read length and coverage, what is the expected contig length that an assembler would produce on a given genome? The foundational work of Lander and Waterman tackled this question, but their method is not applicable to modern high-throughput sequencing. In this paper, we derive what we call a Z-value, which is a formula that takes as input the read length, coverage, and basic properties of the genome, and returns a prediction of the mean contig length produced by a simple single-k assembler on error-free data. We show on a benchmark of 14 genomes that the Z-value is highly accurate, with a mean absolute prediction error of less than 2 percent. We further show how this formula can be used to determine the best choice of k for the assembler and how to choose a coverage level that gives contig lengths within a desired fraction of the optimal. Finally, we show how the Z-value can also predict the performance of a more complicated assembler like Velvet and how it can be used to guide the choice between instruments when there is a tradeoff between coverage and read length and the budget is limited.
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BibTeX
@misc{abrar2026theoretical,
title = {{Theoretical prediction of assembly contiguity}},
author = {M. H. Abrar and P. Medvedev and A. Novikov and K. Sahlin},
howpublished = {bioRxiv},
year = {2026},
month = nov,
doi = {10.64898/2026.11.05.764522},
url = {https://www.biorxiv.org/content/10.64898/2026.11.05.764522v1},
note = {CC BY},
}
RIS
TY - UNPB
TI - Theoretical prediction of assembly contiguity
AU - M. H. Abrar
AU - P. Medvedev
AU - A. Novikov
AU - K. Sahlin
PY - 2026
DA - 2026/11/05
PB - bioRxiv
DO - 10.64898/2026.11.05.764522
UR - https://www.biorxiv.org/content/10.64898/2026.11.05.764522v1
AB - Theoretical methods for predicting the performance of assembly algorithms have the potential to guide experimental design on a scale that simulations cannot. A fundamental question of experimental design is how deep to sequence in order to obtain an assembly with long-enough contigs. More precisely, given a certain read length and coverage, what is the expected contig length that an assembler would produce on a given genome? The foundational work of Lander and Waterman tackled this question, but their method is not applicable to modern high-throughput sequencing. In this paper, we derive what we call a Z-value, which is a formula that takes as input the read length, coverage, and basic properties of the genome, and returns a prediction of the mean contig length produced by a simple single-k assembler on error-free data. We show on a benchmark of 14 genomes that the Z-value is highly accurate, with a mean absolute prediction error of less than 2 percent. We further show how this formula can be used to determine the best choice of k for the assembler and how to choose a coverage level that gives contig lengths within a desired fraction of the optimal. Finally, we show how the Z-value can also predict the performance of a more complicated assembler like Velvet and how it can be used to guide the choice between instruments when there is a tradeoff between coverage and read length and the budget is limited.
ER -