Array Quality

The application for array quality is to provide guidance and valuable insights into quality control for the protein microarray. A protein microarray or also named as protein chip is a high-throughput method used to track the interactions and activities of proteins, and to determine their function, and determining function on a large scale (Melton, 2004). Its main advantage lies in the fact that large numbers of proteins can be tracked in parallel. The chip consists of a support surface such as a glass slide, nitrocellulose membrane, bead, or microtitre plate, to which an array of capture proteins is bound (Schena, 2005). Protein microarrays are rapid, automated, economical, and highly sensitive, consuming small quantities of samples and reagents (Mitchell, 2004). The high-throughput technology behind the protein microarray was relatively easy to develop since it is based on the technology developed for DNA microarrays (Hall, Ptacek and Snyder, 2012)which have become the most widely used microarrays.


-Melton, L.(2004). Protein arrays: Proteomics in multiplex. Nature. 429 (6987):pp101-107. ISSN 0028-0836

-Schena, M. (2005). Protein Microarrays. Jones & Bartlett Learning. p47. ISBN 978-0-7637-3127-4.

-Mitchell, P(2002). A perspective on protein microarrays. Nature Biotechnology. 20 (3): pp225-229. ISSN 1087-0156

-Hall, DA; Ptacek, J. and Snyder, M. (December 12, 2012). Protein Microarray Technology. Mech. Ageing Dev. 128(1):pp161-167. PMC 1828913

-Kauffmann, A.and Huber, W. (2013). Introduction: Microarray Quality Assessment with ArrayQualityMetrics, p1-7.

-(2017). DNA microarray. Retrieved 1st August, 2017, from

Single-channel microarrays, also called one-color microarrays, are designed to give estimations of the absolute levels of gene expression. Protetermed a protein function array, will consist of thousands of native proteins immobilized in a defined pattern. Such arrays can be utilized for massively parallel testing of protein function, hence the name.

Our array quality application allows the user to upload the .gpr file extension which is developed by Molecular Devices and is used for files created using the platform of GenePix Pro software. GenePix Pro software is a tool used mainly used for biological experiments, and pieces of data gathered from these experiments are saved in files with the .gpr format.Files in this format can be read from the Molecular Devices GenePix Pro software, Microsoft Excel 2010 or any text editor. You can download the GenePix Pro 7 Microarray Acquisition and Analysis Software here .


-(2010, December 12).GenePix Pro 7 Microarray Acquisition & Analysis Software Download Page,Retrieved 18th September,2017, from

-(2017). ReviverSoft,Retrieved 21st September,2017, from

Two-color microarrays are typically hybridized with cDNA prepared from two samples that the researchers wish to compare (such as diseased tissue versus healthy tissue). These samples are labeled with two different fluorophores. Fluorescent dyes commonly used for cDNA labelling include Cy3, which has a fluorescence emission wavelength of 570 nm (corresponding to the green part of the light spectrum), and Cy5 with a fluorescence emission wavelength of 670 nm (corresponding to the red part of the light spectrum). The two Cy-labelled cDNA samples are mixed and hybridized to a single microarray that is then scanned in a microarray scanner to visualize fluorescence of the two fluorophores after excitation with a laser beam of a defined wavelength. Relative intensities of each fluorophore may then be used in ratio-based analysis to identify up-regulated and down-regulated genes. Oligonucleotide microarrays often contain control probes designed to hybridize with RNA spike-ins. The degree of hybridization between the spike-ins and the control probes is used to normalize the hybridization measurements for the target probes. Although absolute levels of gene expression may be determined using the two-color array system, the system is more apt for the determination of relative differences in expression among different spots within a sample and between samples.



Shiny Application Development

  • School of Mathematics and Statistics, University of Sydney
    • Yingxin Lin
    • Taiyun Kim
    • Irene Rui Chen


  • Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University
    • Sheng-ce Tao, Ph.D., Professor, Vice Dean
    • Yang Li


This application is designed to process the analysis for protein one-colour array and two colour array. For both protein one-colour array and two colour array, examples are provided for the user. There are five examples for protein one-colour array and there are six example for two colour array. The examples are the type of gpr files.The user can upload their own dateset (in gpr file format) to check the qualityand score of each dataset. Our QC application gives user a numeric QC score for the input data by utilising ridge regression model created in our current database. The user can also choose to include their input data to the database for their future run to improve the model prediction.

The output plots are provided for the user to assist their evaluation of the array quality. Also, the boxplot is to visualise where the input data QC measures sit compared to the database. This is to give an overview of which QC measures are failing. More detailed information can be found in the Demonstration of Protein one-colour array and two colour array.

Explanation for Quality Score

Explanation of Boxplot

Explanation for MA Plot

When the user chooce to see the

Explanation for Image of Log Intesity

- Plotting according to the Ranked/Initial Values

One Colour Array Quality

Array Quality Score:

The higher score shows the better array quality.

It can be counted as a relatively good array quality if the score is equal or greater than 7.

Click below to contribute your data to the model for future improvement.

Box plot of file features compared to the model

MA Plot

Image of Foreground Log Intesity

Image of Background Log Intensity

Two Colour Array Quality

MA Plot

MA Plot After Normalization

Image of M Values

Image of Red Background Intensity Plot

Image of Green Background Intensity Plot

Boxplot of the array Quality

Mass Spectrometry Quality Control

Classification / Score

e.g. Good? Bad? Intermediate?

Feature Comparison

Box plot