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Table 3 Main types of statistical methods applied in microarray data analysis studies.

From: An assessment of recently published gene expression data analyses: reporting experimental design and statistical factors

Technique

Application papers (%)*

Methodology papers (%)

t-test

21 (14.89)

11 (7.24)

ANOVA

47 (33.33)

22 (14.47)

Data clustering

56 (39.72)

75 (49.34)

Supervised classification

5 (3.55)

37 (24.34)

Mixed classification models

3 (2.13)

12 (7.89)

Nonparametric tests

11 (7.80)

6 (3.95)

Regression analysis

7 (4.96)

11 (7.24)

Correlation-based analyses

23 (16.31)

4 (2.63)

Fuzzy logic methods

0 (0.00)

4 (2.63)

Fisher-exact tests

5 (3.55)

5 (3.29)

PCA

7 (7.96)

4 (2.63)

Discriminant analysis

4 (2.84)

4 (2.63)

Time series analysis

0 (0.00)

6 (3.95)

Meta analysis

2 (1.42)

1 (0.66)

Other methods

9 (6.63)

22 (14.47)

  1. * Percentages calculated in relation to each paper category separately. For example, in connection to the use of t-test in application papers, the table indicates that 21 application papers (out of 141), i.e. 14.89 %, used this technique.