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Optimisation of ForenSeq STR data analysis with FDSTools and comparative analysis with UAS
University of Skövde, School of Bioscience.
2021 (English)Independent thesis Advanced level (degree of Master (Two Years)), 30 credits / 45 HE creditsStudent thesis
Abstract [en]

DNA profiling with short tandem repeat data generated with massively parallel sequencing is associated with several challenges. FDSTools is an open-source software which applies correction models based on a reference database to correct DNA profiles. The correction models aim to provide an accurate representation of the true DNA profile and associated artefacts. Low analytical thresholds in FDSTools are suggested to improve detection of minor profiles in complex mixtures. The objective was to optimise FDSTools analysis for ForenSeq data, and to establish a Swedish reference database. The FDSTools analysis was subsequently compared to default analysis with the commercial Universal Analysis Software, and the likelihood ratio was evaluated. The FDSTools Library file was adapted for ForenSeq data. FASTQ files from single- and mixed-source samples were analysed with the software. The concordance between the software was assessed, and analytical thresholds in FDSTools were optimised. Likelihood ratios were calculated for sequencing- and capillary electrophoresis data to investigate the benefit of sequence level information. A reference database and correction models could not be generated, meaning that uncorrected data was used. The two software showed a 98.5% concordance. Disconcordance was caused by allele drop-out in heterozygous loci which implicated that certain markers may require individual interpretation. Lowering the analytical thresholds in FDSTools appeared to improve mixture deconvolution, but the lack of correction models obscured interpretation. Hence, without correction models optimial analytical thresholds could not be defined. Likelihood ratio based on sequencing data was not consistently higher compared to capillary electrophoresis, suggesting that sequence information is not always advantageous.

Place, publisher, year, edition, pages
2021. , p. 38
National Category
Bioinformatics and Systems Biology
Identifiers
URN: urn:nbn:se:his:diva-20053OAI: oai:DiVA.org:his-20053DiVA, id: diva2:1575283
External cooperation
Nationellt Forensiskt Centrum (NFC)
Subject / course
Systems Biology
Educational program
Biomarkers in Molecular Medicine - Master's Programme 120 ECTS
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Available from: 2021-06-29 Created: 2021-06-29 Last updated: 2021-06-29Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
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