Statistical quality control analysis of high-dimensional omics data
by Yongkang Kim; Gyu-Tae Kim; Min-Seok Kwon; Taesung Park
International Journal of Data Mining and Bioinformatics (IJDMB), Vol. 18, No. 3, 2017

Abstract: Quality control (QC) is a most important pre-processing procedure to remove unwanted variation in omics data, such as microarray, next generation sequencing, and mass spectrometry data. QC has become a standard procedure for identifying important biological 'signatures' of interest. Although several QC analysis tools are now used widely, these usually require a subjective guideline to determine the quality of the omics data being assessed. Here, we propose a new simple QC plot for high-dimensional omics data that can identify samples of poor quality in a more objective manner. The proposed QC plot can easily identify samples of poor quality by comparing the between/within group distances, between all possible pairs of samples. Through a permutation procedure, the distribution of these distances is derived, generating p-values for each sample. These p-values can then be used as a more objective criterion to determine the quality of the sample. To exemplify the utility of this approach, we applied the proposed QC plot to MicroArray Quality Control (MAQC), project 1 data.

Online publication date: Fri, 06-Oct-2017

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Data Mining and Bioinformatics (IJDMB):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com