Statistical Analysis of Microarray Data

We have presented all data as mean ± standard error. Once chips passed the quality control criteria, we evaluated them with Partek (Partek, St. Louis), which is commercial software specifically designed to analyze microarray data. Using Partek, we conducted ANOVA analysis and reported the p-values of comparisons of interest, as previously described [5 (link)]. We adopted Student’s t-test or one-way ANOVA as necessary to evaluate the quantitative data and the paired sample t-test to evaluate any data changes before and after IVIG treatment. All statistical analyses were carried out with SPSS version 12.0 for Windows XP (SPSS, Inc., Chicago, USA), and we considered a two-sided p-value less than 0.05 statistically significant.

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Huang Y.H., Lo M.H., Cai X.Y, & Kuo H.C. (2018). Epigenetic hypomethylation and upregulation of NLRC4 and NLRP12 in Kawasaki disease. Oncotarget, 9(27), 18939-18948.

Publication 2018

SPSS version 12.0 for Windows XP

Anova Chips Ivig Microarray Student

Corresponding Organization :

Other organizations : Kaohsiung Chang Gung Memorial Hospital, Chang Gung University, Chiayi Chang Gung Memorial Hospital

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Variable analysis

independent variables

IVIG treatment

dependent variables

Gene expression (evaluated using microarray analysis)

control variables

Quality control criteria for chips

controls

Positive controls: Not explicitly mentioned
Negative controls: Not explicitly mentioned

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