MicroRNA Profiling of Fresh Lung Adenocarcinoma and Adjacent Normal Tissues from Ten Korean Patients Using miRNA-Seq
- 주제(키워드) deep learning , Korean patients , lung adenocarcinoma , microRNA , miRNA-seq , next-generation sequencing , Wx
- 등재 SCOPUS
- OA유형 All Open Access; Gold Open Access
- 발행기관 MDPI
- 발행년도 2023
- 총서유형 Journal
- URI http://www.dcollection.net/handler/ewha/000000209579
- 본문언어 영어
- Published As https://doi.org/10.3390/data8060094
초록/요약
MicroRNA transcriptomes from fresh tumors and the adjacent normal tissues were profiled in 10 Korean patients diagnosed with lung adenocarcinoma using a next-generation sequencing (NGS) technique called miRNA-seq. The sequencing quality was assessed using FastQC, and low-quality or adapter-contaminated portions of the reads were removed using Trim Galore. Quality-assured reads were analyzed using miRDeep2 and Bowtie. The abundance of known miRNAs was estimated using the reads per million (RPM) normalization method. Subsequently, using DESeq2 and Wx, we identified differentially expressed miRNAs and potential miRNA biomarkers for lung adenocarcinoma tissues compared to adjacent normal tissues, respectively. We defined reliable miRNA biomarkers for lung adenocarcinoma as those detected by both methods. The miRNA-seq data are available in the Gene Expression Omnibus (GEO) database under accession number GSE196633, and all processed data can be accessed via the Mendeley data website. Dataset: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE196633 and https://data.mendeley.com/datasets/vp977psjcb/2. Dataset License: CC0 © 2023 by the authors.
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