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MicroRNA Profiling of Fresh Lung Adenocarcinoma and Adjacent Normal Tissues from Ten Korean Patients Using miRNA-Seq

Title
MicroRNA Profiling of Fresh Lung Adenocarcinoma and Adjacent Normal Tissues from Ten Korean Patients Using miRNA-Seq
Authors
Park J.Na S.J.Yoon J.S.Kim S.Chun S.H.Kim J.J.Kim Y.-D.Ahn Y.-H.Kang K.Ko Y.H.
Ewha Authors
안영호
SCOPUS Author ID
안영호scopus
Issue Date
2023
Journal Title
Data
ISSN
2306-5729JCR Link
Citation
Data vol. 8, no. 6
Keywords
deep learningKorean patientslung adenocarcinomamicroRNAmiRNA-seqnext-generation sequencingWx
Publisher
MDPI
Indexed
SCOPUS scopus
Document Type
Article
Abstract
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.
DOI
10.3390/data8060094
Appears in Collections:
의과대학 > 의학과 > Journal papers
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