Selection of Optimal Bioinformatic Tools and Proper Reference for Reducing the Alignment Error in Targeted Sequencing Data
| Autor: | Mohammad Amin Tabatabaiefar, Mohammadreza Sehhati, Hannane Mohammadi Nodehi |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
lcsh:Medical technology
Radiological and Ultrasound Technology sequence analysis Sequence analysis Computer science Sequencing data Biomedical Engineering Health Informatics Computational biology Genome Chromosomes 030218 nuclear medicine & medical imaging 03 medical and health sciences 0302 clinical medicine lcsh:R855-855.5 030220 oncology & carcinogenesis Mutation (genetic algorithm) Computer Science (miscellaneous) Coding region Radiology Nuclear Medicine and imaging Human genome Original Article high-throughput nucleotide sequencing Selection (genetic algorithm) Reference genome |
| Zdroj: | Journal of Medical Signals and Sensors Journal of Medical Signals and Sensors, Vol 11, Iss 1, Pp 37-44 (2021) |
| ISSN: | 2228-7477 |
| Popis: | Background: Careful design in the primary steps of a next-generation sequencing study is critical for obtaining successful results in downstream analysis. Subjects and Methods: In this study, a framework is proposed to evaluate and improve the sequence mapping in targeted regions of the reference genome. In this regard, simulated short reads were produced from the coding regions of the human genome and mapped to a Customized Target-Based Reference (CTBR) by the alignment tools that have been introduced recently. The short reads produced by different sequencing technologies aligned to the standard genome and also CTBR with and without well-defined mutation types where the amount of unmapped and misaligned reads and runtime was measured for comparison. Results: The results showed that the mapping accuracy of the reads generated from Illumina Hiseq2500 using Stampy as the alignment tool whenever the CTBR was used as reference was significantly better than other evaluated pipelines. Using CTBR for alignment significantly decreased the mapping error in comparison to other expanded or more limited references. While intentional mutations were imported in the reads, Stampy showed the minimum error of 1.67% using CTBR. However, the lowest error obtained by stampy too using whole genome and one chromosome as references was 3.78% and 20%, respectively. Maximum and minimum misalignment errors were observed on chromosome Y and 20, respectively. Conclusion: Therefore using the proposed framework in a clinical targeted sequencing study may lead to predict the error and improve the performance of variant calling regarding the genomic regions targeted in a clinical study. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|