RNA-seq reveals more consistent reference genes for gene expression studies in human non-melanoma skin cancers

Clicks: 253
ID: 99334
2017
Free PDF
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal
Steady

Ranked #91 of 189 articles by views in PeerJ

Most read Least read

Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 189 in total.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Sign in to mint
Abstract
Identification of appropriate reference genes (RGs) is critical to accurate data interpretation in quantitative real-time PCR (qPCR) experiments. In this study, we have utilised next generation RNA sequencing (RNA-seq) to analyse the transcriptome of a panel of non-melanoma skin cancer lesions, identifying genes that are consistently expressed across all samples. Genes encoding ribosomal proteins were amongst the most stable in this dataset. Validation of this RNA-seq data was examined using qPCR to confirm the suitability of a set of highly stable genes for use as qPCR RGs. These genes will provide a valuable resource for the normalisation of qPCR data for the analysis of non-melanoma skin cancer.
Reference Key
hoang2017rnaseqpeerj Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Hoang, Van L.T.;Tom, Lisa N.;Quek, Xiu-Cheng;Tan, Jean-Marie;Payne, Elizabeth J.;Lin, Lynlee L.;Sinnya, Sudipta;Raphael, Anthony P.;Lambie, Duncan;Frazer, Ian H.;Dinger, Marcel E.;Soyer, H. Peter;Prow, Tarl W.;
Journal PeerJ
Year 2017
DOI
DOI not found
URL
https://peerj.com/articles/3631.pdf
Keywords
Medicine personnel management. employment management

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

Comments

No comments yet. Be the first to comment on this article.