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Statistical Analysis

This module offers various commonly used statistical and machine learning methods including t-tests, ANOVA, PCA, PLS-DA and Orthogonal PLS-DA. It also provides clustering and visualization tools to create dendrograms and heatmaps as well as to classify data based on random forests and SVM.
本模块提供了各种常用的统计和机器学习方法，包括t检验，方差分析，PCA, PLS-DA和正交PLS-DA。它还提供了聚类和可视化工具来创建树状图和热图，以及根据随机森林和SVM对数据进行分类。

1.上传数据

Fig1.PNG

如果你上传的列表中每一列为一个样本，Format选择Samples in columns；如果每一行为一个样本，Format选择Samples in rows
点击Submit

2数据完整性检查

Data Integrity Check:

捕获.PNG

3.数据过滤

捕获3.PNG

Data Filtering:
Filtering features if their RSDs are > 25%
Interquantile range (IQR)

4标准化总览

Normalization overview:

捕获2.PNG

点击proceed