PT  - JOURNAL ARTICLE
AU  - Mehmet Akdel
AU  - Henri van de Geest
AU  - Elio Schijlen
AU  - Irma M.H. van Rijswijck
AU  - Eddy J. Smid
AU  - Gabino Sanchez-Perez
AU  - Dick de Ridder
TI  - Signal-based optical map alignment
AID  - 10.1101/2021.06.01.446540
DP  - 2021 Jan 01
TA  - bioRxiv
PG  - 2021.06.01.446540
4099  - http://biorxiv.org/content/early/2021/06/02/2021.06.01.446540.short
4100  - http://biorxiv.org/content/early/2021/06/02/2021.06.01.446540.full
AB  - In genomics, optical mapping technology provides long-range contiguity information to improve genome sequence assemblies and detect structural variation. Originally a laborious manual process, Bionano Genomics platforms now offer high-throughput, automated optical mapping based on chips packed with nanochannels through which unwound DNA is guided and the fluorescent DNA backbone and specific restriction sites are recorded. Although the raw image data obtained is of high quality, the processing and assembly software accompanying the platforms is closed source and does not seem to make full use of data, labeling approximately half of the measured signals as unusable. Here we introduce two new software tools, independent of Bionano Genomics software, to extract and process molecules from raw images (OptiScan) and to perform molecule-to-molecule and molecule-to-reference alignments using a novel signal-based approach (OptiMap). We demonstrate that the molecules detected by OptiScan can yield better assemblies, and that the approach taken by OptiMap results in higher use of molecules from the raw data. These tools lay the foundation for a suite of open-source methods to process and analyze high-throughput optical mapping data. The Python implementations of the OptiTools are publicly available through http://www.bif.wur.nl/.Competing Interest StatementThe authors have declared no competing interest.