Optimizing of pre-processing analysis for Illumina RNA-Seq data in Arabidopsis thaliana

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but.event.date23.04.2024cs
but.event.titleSTUDENT EEICT 2024cs
dc.contributor.authorSchwarzerová, Jana
dc.contributor.authorJanigová, Patrícia
dc.contributor.authorDvořáčková, Martina
dc.contributor.authorWeckwerth, Wolfram
dc.date.accessioned2024-07-09T07:47:49Z
dc.date.available2024-07-09T07:47:49Z
dc.date.issued2024cs
dc.description.abstractGene expression analysis through RNA sequencing (RNA-Seq) has revolutionized molecular biology, providing profound insights into the intricate transcriptional landscapes of organisms. Arabidopsis thaliana, a widely studied model plant, serves as a cornerstone for investigating fundamental biological and ecology processes. However, accurate interpretation of RNASeq data hinges on meticulous pre-processing methods to ensure data integrity and trustworthiness, especially in the context of Illumina sequencing. In this research, we present a comprehensive framework for optimizing pre-processing analysis tailored specifically for Arabidopsis thaliana RNA-Seq datasets generated through Illumina sequencing. Our approach encompasses rigorous quality control, precise read alignment, transcript quantification, and normalization procedures crucial for subsequent differential expression analysis. Additionally, we address unique considerations and challenges inherent to Arabidopsis thaliana datasets, providing valuable insights for researchers in the field.en
dc.formattextcs
dc.format.extent142-145cs
dc.format.mimetypeapplication/pdfen
dc.identifier.citationProceedings II of the 30st Conference STUDENT EEICT 2024: Selected papers. s. 142-145. ISBN 978-80-214-6230-4cs
dc.identifier.doi10.13164/eeict.2024.142
dc.identifier.isbn978-80-214-6230-4
dc.identifier.issn2788-1334
dc.identifier.urihttps://hdl.handle.net/11012/249302
dc.language.isoencs
dc.publisherVysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologiícs
dc.relation.ispartofProceedings II of the 30st Conference STUDENT EEICT 2024: Selected papersen
dc.relation.urihttps://www.eeict.cz/eeict_download/archiv/sborniky/EEICT_2024_sbornik_2.pdfcs
dc.rights© Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologiícs
dc.rights.accessopenAccessen
dc.subjectGene expression analysisen
dc.subjectQuality controlen
dc.subjectArabidopsis thalianaen
dc.subjectTranscriptomicsen
dc.titleOptimizing of pre-processing analysis for Illumina RNA-Seq data in Arabidopsis thalianaen
dc.type.driverconferenceObjecten
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen
eprints.affiliatedInstitution.departmentFakulta elektrotechniky a komunikačních technologiícs
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