A post-processing algorithm for miRNA microarray data

• Verfasst von: Nersisyan, Stepan [VerfasserIn]
• Verfasst von: Turchinovich, Andrey [VerfasserIn]
• Verfasst von: Burwinkel, Barbara [VerfasserIn]
• Titel: A post-processing algorithm for miRNA microarray data
• Verf.angabe: Stepan Nersisyan, Maxim Shkurnikov, Andrey Poloznikov, Andrey Turchinovich, Barbara Burwinkel, Nikita Anisimov and Alexander Tonevitsky
• E-Jahr: 2020
• Jahr: 12 February 2020
• Umfang: 9 S.
• Fussnoten: Gesehen am 08.07.2020
• Titel Quelle: Enthalten in: International journal of molecular sciences
• Ort Quelle: Basel : Molecular Diversity Preservation International, 2000
• Jahr Quelle: 2020
• Band/Heft Quelle: 21(2020,4) Artikel-Nummer 1228, 9 Seiten
• ISSN Quelle: 1422-0067
• ISSN Quelle: 1661-6596
• DOI: doi:10.3390/ijms21041228
• Datenträger: Online-Ressource
• Sprache: eng
• Sach-SW: miRNA microarrays
• Sach-SW: miRNome of breast cancer
• Sach-SW: TCGA
• K10plus-PPN: 1696945100

Abstract

One of the main disadvantages of using DNA microarrays for miRNA expression profiling is the inability of adequate comparison of expression values across different miRNAs. This leads to a large amount of miRNAs with high scores which are actually not expressed in examined samples, i.e., false positives. We propose a post-processing algorithm which performs scoring of miRNAs in the results of microarray analysis based on expression values, time of discovery of miRNA, and correlation level between the expressions of miRNA and corresponding pre-miRNA in considered samples. The algorithm was successfully validated by the comparison of the results of its application to miRNA microarray breast tumor samples with publicly available miRNA-seq breast tumor data. Additionally, we obtained possible reasons why miRNA can appear as a false positive in microarray study using paired miRNA sequencing and array data. The use of DNA microarrays for estimating miRNA expression profile is limited by several factors. One of them consists of problems with comparing expression values of different miRNAs. In this work, we show that situation can be significantly improved if some additional information is taken into consideration in a comparison.