An Error Correction and DeNovo Assembly Approach for Nanopore Reads Using Short Reads

Author(s): Mehdi Kchouk, Mourad Elloumi*.

Journal Name: Current Bioinformatics

Volume 13 , Issue 3 , 2018

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Graphical Abstract:


Background: Error Correction is an important task in the analysis and manipulations of NGS data. The purpose of error correction is to facilitate data analysis for large projects like de novo assembly project. Here we present a new hybrid algorithm for error correction of long reads using short reads. Our algorithm can be flexibly adapted to different types of errors. Next, we make a de novo assembly for corrected long reads.

Objective: We present MiRCA (MinIon Reads Correction Algorithm) a hybrid approach based on the sequences alignments that detects and corrects errors for MinIon long reads using Illumina short reads.

Methods: In our approach, we operate in four steps. First, we make a Quality Control and Cleaning data. Second, we use the contig forming for the Pre-Error Correction Step. Third, we use the alignment to align pre-assembled contig to long reads and we use this alignment to correction erroneous long reads. Finally, we do an assembly for the corrected long reads.

Results: The results of mapping of S.cerevisaeW303 and E.coli genomes shows that our error correction approach produce a high quality long reads with mapping rate ~99% to the reference genome in reasonable time. For denovo assembly, the corrected long reads gives good assembly in a short running time compared to other error correction tools.

Conclusion: MiRCA is a new hybrid approach that detects and corrects errors. It uses an alignmentbased approach using pre-assembled short reads as a reference to correct nanopore long reads. The experimental evaluation of the corrected long reads on the reference genome of S. cerevisae and E.coli shows that MiRCA ensures best error correction compared to existing related works.

Keywords: Error Correction, de novo assembly, long reads, short reads, minion, illumina, NGS, algorithm.

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Article Details

Year: 2018
Page: [241 - 252]
Pages: 12
DOI: 10.2174/1574893612666170530073736
Price: $65

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