Matteo Manica, Loic Kwate Dassi, et al.
ISGC 2022
We carried out a series of replicate experiments on DNA microarrays using two cell lines and two technologies-the Agilent Human 1A Microarray and the GE Amersham Codelink Uniset Human 20K I Bioarray. We demonstrated that quantifying the noise level as a function of signal strength allows identification of the absolute and differential mRNA expression levels at which biological variability can be resolved above measurement noise. This represents a new formulation of a sensitivity threshold that can be used to compare platforms. It was found that the correlation in expression level between platforms is considerably worse than the correlation between replicate measurements taken using the same platform. In addition, we carried out replicate measurements at different stages of sample processing. This novel approach enables us to quantify the noise introduced into the measurements at each step of the experimental protocol. We demonstrated how this information can be used to determine the most efficient means of using replicates to reduce experimental uncertainty. © Mary Ann Liebert, Inc.
Matteo Manica, Loic Kwate Dassi, et al.
ISGC 2022
Qing Zhong, Rui Sun, et al.
Life Science Alliance
Iago Pereiro Pereiro, Julien Aubert, et al.
Biomicrofluidics
Ella Barkan, Ibrahim Siddiqui, et al.
Computational And Structural Biotechnology Journal