Optical map transformations

1974 ◽  
Vol 10 (2) ◽  
pp. 164-168 ◽  
Author(s):  
Olof Bryngdahl
2017 ◽  
Vol 33 (17) ◽  
pp. 2740-2742 ◽  
Author(s):  
Giles Miclotte ◽  
Stéphane Plaisance ◽  
Stephane Rombauts ◽  
Yves Van de Peer ◽  
Pieter Audenaert ◽  
...  
Keyword(s):  

2020 ◽  
Vol 27 (4) ◽  
pp. 519-533 ◽  
Author(s):  
Weihua Pan ◽  
Tao Jiang ◽  
Stefano Lonardi

2019 ◽  
Vol 14 (1) ◽  
Author(s):  
Martin D. Muggli ◽  
Simon J. Puglisi ◽  
Christina Boucher

Abstract Background Genome-wide optical maps are ordered high-resolution restriction maps that give the position of occurrence of restriction cut sites corresponding to one or more restriction enzymes. These genome-wide optical maps are assembled using an overlap-layout-consensus approach using raw optical map data, which are referred to as Rmaps. Due to the high error-rate of Rmap data, finding the overlap between Rmaps remains challenging. Results We present Kohdista, which is an index-based algorithm for finding pairwise alignments between single molecule maps (Rmaps). The novelty of our approach is the formulation of the alignment problem as automaton path matching, and the application of modern index-based data structures. In particular, we combine the use of the Generalized Compressed Suffix Array (GCSA) index with the wavelet tree in order to build Kohdista. We validate Kohdista on simulated E. coli data, showing the approach successfully finds alignments between Rmaps simulated from overlapping genomic regions. Conclusion we demonstrate Kohdista is the only method that is capable of finding a significant number of high quality pairwise Rmap alignments for large eukaryote organisms in reasonable time.


Neuroscience ◽  
2005 ◽  
Vol 136 (3) ◽  
pp. 681-695 ◽  
Author(s):  
J.G. Bjaalie ◽  
T.B. Leergaard ◽  
S. Lillehaug ◽  
F. Odeh ◽  
I.A. Moene ◽  
...  

1983 ◽  
Vol 22 (6) ◽  
pp. 780 ◽  
Author(s):  
A. W. Lohmann ◽  
N. Streibl
Keyword(s):  

2010 ◽  
pp. S71-S80
Author(s):  
J Kolářová ◽  
K Fialová ◽  
O Janoušek ◽  
M Nováková ◽  
I Provazník

Monophasic action potential (MAP) can be recorded from the heart surface by optical method based on fluorescence measurement. The motion of isolated heart during experiment caused additional noise in recorded signal. The motion artifact can be eliminated by ratiometric fluorescence emission measurements. This study is based on experiments in which optical MAP measurement is done by single-wavelength and dualwavelength measurement of fluorescence emission. Both recording setups are presented and their advantages and disadvantages are discussed. MAPs recorded by both methods from isolated rabbit hearts perfused according to Langendorff are presented. Simultaneous electrograms (EG) and MAPs recording are analyzed and measurement of velocity of impulse conduction through heart tissue is presented.


2019 ◽  
Author(s):  
Weihua Pan ◽  
Tao Jiang ◽  
Stefano Lonardi

AbstractDue to the current limitations of sequencing technologies,de novogenome assembly is typically carried out in two stages, namely contig (sequence) assembly and scaffolding. While scaffolding is computationally easier than sequence assembly, the scaffolding problem can be challenging due to the high repetitive content of eukaryotic genomes, possible mis-joins in assembled contigs and inaccuracies in the linkage information. Genome scaffolding tools either use paired-end/mate-pair/linked/Hi-C reads or genome-wide maps (optical, physical or genetic) as linkage information. Optical maps (in particular Bionano Genomics maps) have been extensively used in many recent large-scale genome assembly projects (e.g., goat, apple, barley, maize, quinoa, sea bass, among others). However, the most commonly used scaffolding tools have a serious limitation: they can only deal with one optical map at a time, forcing users to alternate or iterate over multiple maps. In this paper, we introduce a novel scaffolding algorithm called OMGS that for the first time can take advantages of multiple optical maps. OMGS solves several optimization problems to generate scaffolds with optimal contiguity and correctness. Extensive experimental results demonstrate that our tool outperforms existing methods when multiple optical maps are available, and produces comparable scaffolds using a single optical map. OMGS can be obtained fromhttps://github.com/ucrbioinfo/OMGS


2021 ◽  
Author(s):  
Mehmet Akdel ◽  
Henri van de Geest ◽  
Elio Schijlen ◽  
Irma M.H. van Rijswijck ◽  
Eddy J. Smid ◽  
...  

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/.


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