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DOI 10.1007/978-3-030-58814-4_63
Error Correction in Nanopore Reads for de novo Genomic Assembly
2020
Aldridge-Aguila, Jacqueline
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Alvarez-Saravia, Diego
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Navarrete Signorile, Marcelo Alejandro
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Uribe Paredes, Roberto Alex
The purpose of genome sequencing is to determine the DNA sequence of a given organism. Current sequencing technologies can be classified by the type of output data. Whereas Nanopore technology generates long reads with high error rates, short read technologies - such as Illumina sequencing - generate shorter reads but with low error rate. Since de novo genome assembly of sequencing reads is defined as a NP-hard problem, it remains as one of the major challenges for defining reference genomes of different species. This paper aims to improve the quality of reads obtained through Oxford Nanopore Technologies (ONT). We developed an algorithm to associate the reads obtained from Illumina with the ones obtained with Nanopore. Low accuracy ONT reads were corrected with the high quality Illumina reads to achieve an improved sequencing data. The inclusion of this algorithm as a preprocessing step resulted in improved coverage, contig length, and mismatch rate when performing de novo genome assembly of a bacterial genome with well known tools.
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DOI 10.1007/978-3-030-17938-0_27
Identification of Immunoglobulin Gene Usage in Immune Repertoires Sequenced by Nanopore Technology
2019
Ahumada-Garcia, Roberto
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Gonzalez-Puelma, Jorge
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Alvarez-Saravia, Diego
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Barrientos, Ricardo J.
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Uribe Paredes, Roberto Alex
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Lopez-Cortes, Xaviera A.
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Navarrete Signorile, Marcelo Alejandro
The immunoglobulin receptor represents a central molecule in acquired immunity. The complete set of immunoglobulins present in an individual is known as immunological repertoire. The identification of this repertoire is particularly relevant in immunology and cancer research and diagnostics. In a seminal work we provided a proof of concept of the novel ARTISAN-PCR amplification method, we adapted this technology for sequencing using Nanopore technology. This approach may represent a faster, more portable and costeffective alternative to current methods. In this study we present the pipeline for the analysis of immunological repertoires obtained by this approach. This paper shows the performance of immune repertoires sequenced by Nanopore technology, using measures of error, coverage and gene usage identification. In the bioinformatic methodology used in this study, first, Albacore Base calling software, was used to translate the electrical signal of Nanopore to DNA bases. Subsequently, the sequons, introduced during amplification, were aligned using bl2seq from Blast. Finally, selected reads were mapped using IMGT/ HighV-QUEST and IgBlast. Our results demonstrate the feasibility of immune repertoire sequencing by Nanopore technology, obtaining higher depth than PacBio sequencing and better coverage than pair-end based technologies. However, the high rate of systematic errors indicates the need of improvements in the analysis pipeline, sequencing chemistry and/or molecular amplification.
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DOI 10.1109/sccc49216.2019.8966421
Pattern recognition on antigen-antibody interactions from protein microarrays based on data mining and bioinformatics analysis
2019-11-1
Torres-Almonacid, Jorge
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Medina-Ortiz, David
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Alvarez-Saravia, Diego
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Aguila Guerrero, Julio Jose
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Olivera-Nappa, Alvaro
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Navarrete Signorile, Marcelo Alejandro
Understanding the mechanisms of interaction between antigen-antibody systems is one of the most relevant problems in the field of Immunology, since, supported by computational tools and data mining techniques, it would be possible to implement new antibody design tools. As a first approach and taking advantage of microarray techniques, a biological pattern recognition pipeline is presented from multiple ProtoArray chips, based on data mining techniques and bioinformatic analysis. This new approach, proposes 3 key stages in data processing: cleaning, statistical-frequency clustering of antigens and characterization by bioinformatic methods. This methodology was tested in a set of 370,000 interactions (45 antibodies, 8,000 antigens), achieving an effective filtering and grouping, in addition, a group obtained is characterized, in order to test the proposed bioinformatic methods. It is expected that this new method allows the identification of patterns in a simple and efficient way from multidimensional sets generated by protein microarrays.
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Escuela de Medicina

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