Construction of Physical Maps from Oligonucleotide Fingerprints Data

Mayraz, Guy; Shamir, Ron

doi:10.1089/cmb.1999.6.237

Cited by 7 publications

(2 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Twenty years ago, various DNA physical mapping studies (Pevzner, 2000; Rajaraman et al , 2017) analyzed algorithmic problems similar to the CP Problem (Alizadeh et al , 1995; Batzoglou and Istrail, 1999; Mayraz and Shamir, 1999). However, we are not aware of a software tool that resulted from these studies and would be applicable to SSLRs.…”

Section: Methodsmentioning

confidence: 99%

cloudSPAdes: assembly of synthetic long reads using de Bruijn graphs

Tolstoganov

Chen²,

Pevzner

2019

Bioinformatics

View full text Add to dashboard Cite

Motivation The recently developed barcoding-based synthetic long read (SLR) technologies have already found many applications in genome assembly and analysis. However, although some new barcoding protocols are emerging and the range of SLR applications is being expanded, the existing SLR assemblers are optimized for a narrow range of parameters and are not easily extendable to new barcoding technologies and new applications such as metagenomics or hybrid assembly. Results We describe the algorithmic challenge of the SLR assembly and present a cloudSPAdes algorithm for SLR assembly that is based on analyzing the de Bruijn graph of SLRs. We benchmarked cloudSPAdes across various barcoding technologies/applications and demonstrated that it improves on the state-of-the-art SLR assemblers in accuracy and speed. Availability and implementation Source code and installation manual for cloudSPAdes are available at https://github.com/ablab/spades/releases/tag/cloudspades-paper. Supplementary Information Supplementary data are available at Bioinformatics online.

show abstract

Section: Methodsmentioning

confidence: 99%

cloudSPAdes: assembly of synthetic long reads using de Bruijn graphs

Tolstoganov

Chen²,

Pevzner

2019

Bioinformatics

View full text Add to dashboard Cite

show abstract

“…To take this variation into account Nelson et al (2005) [6] proposed to exclude the most abundant bands for reducing the proportion of false overlaps. Other ways of taking into account band frequencies based on Bayes Theorem were also proposed (e.g., [42,43]), but such methods are cumbersome, especially with HICFs (e.g., [44]).…”

Section: Introductionmentioning

confidence: 99%

LTC: a novel algorithm to improve the efficiency of contig assembly for physical mapping in complex genomes

et al. 2010

View full text Add to dashboard Cite

BackgroundPhysical maps are the substrate of genome sequencing and map-based cloning and their construction relies on the accurate assembly of BAC clones into large contigs that are then anchored to genetic maps with molecular markers. High Information Content Fingerprinting has become the method of choice for large and repetitive genomes such as those of maize, barley, and wheat. However, the high level of repeated DNA present in these genomes requires the application of very stringent criteria to ensure a reliable assembly with the FingerPrinted Contig (FPC) software, which often results in short contig lengths (of 3-5 clones before merging) as well as an unreliable assembly in some difficult regions. Difficulties can originate from a non-linear topological structure of clone overlaps, low power of clone ordering algorithms, and the absence of tools to identify sources of gaps in Minimal Tiling Paths (MTPs).ResultsTo address these problems, we propose a novel approach that: (i) reduces the rate of false connections and Q-clones by using a new cutoff calculation method; (ii) obtains reliable clusters robust to the exclusion of single clone or clone overlap; (iii) explores the topological contig structure by considering contigs as networks of clones connected by significant overlaps; (iv) performs iterative clone clustering combined with ordering and order verification using re-sampling methods; and (v) uses global optimization methods for clone ordering and Band Map construction. The elements of this new analytical framework called Linear Topological Contig (LTC) were applied on datasets used previously for the construction of the physical map of wheat chromosome 3B with FPC. The performance of LTC vs. FPC was compared also on the simulated BAC libraries based on the known genome sequences for chromosome 1 of rice and chromosome 1 of maize.ConclusionsThe results show that compared to other methods, LTC enables the construction of highly reliable and longer contigs (5-12 clones before merging), the detection of "weak" connections in contigs and their "repair", and the elongation of contigs obtained by other assembly methods.

show abstract