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

Data(2023)

Cited 0|Views17
No score
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
More
Translated text
Key words
microRNA, lung adenocarcinoma, Korean patients, next-generation sequencing, miRNA-seq, Wx, deep learning
AI Read Science
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined