Microarray lattice method for biological chip

Abstract

The invention discloses a microarray lattice method for a biological chip. According to the method, quasi-Latin square experimental design is adopted and is divided into three kinds: 1, quasi-Latin square array lattice design in sub squares; 2, quasi-Latin square array lattice design among the sub squares; and 3, quasi-Latin square array lattice design in the sub squares and among the sub squares. By the microarray lattice design of the biological chip, space effect error caused by different factors can be avoided and eliminated to a certain degree, and the accuracy of biological experiments or experimental results is improved to a certain degree.

Description

technical field [0001] The invention relates to the field of biotechnology, in particular to a biochip microarray lattice method. Background technique [0002] Academic reports on microarray data analysis methodology mainly focus on the normalization of chip data points after biochip hybridization and systematic error correction to eliminate variation errors from different sources. Yang YH,Dudoit S,Luu P,Lin DM,Peng V,Ngai J,Speed ​​TP.Normalization for cDNA microarray data:a robust composite method addressing single and multiple slide systematic variation.Nucleic Acids Res 2002,30(4): e15. Tarca AL, Cooke JE, Mackay J. A robust neural networks approach for spatial and intensity dependent normalization of cDNA microarray data. Bioinformatics 2005, 21:2674-2683. This is mainly because most of the studies using microarray technology are DNA microarrays, and the DNA microarray chips used can be purchased from biological companies, which saves a very complicated chip productio...

AI Technical Summary

Problems solved by technology

In these three dot arrays, although they are all 12X12 arrays, due to the lack of effective use of biological samples to repeat the design of dot matrix arrays, the errors in the data obtained from the chips spotted by these three spotting methods include Spatial effect errors will affect the final experimental analysis results. If this research is a study of disease detection, it will reduce the detection accuracy to a certain extent.

Images