介绍
PCoA分析采用降维的思想对样本关系进行低维平面的、样本距离矩阵的投影。
使用的程序是R语言的vegan、ade4包
输入
距离文件：
例如
# a1 a2 a3 b1 b2 b3
a1 10 34 51 19 21 31
a2 22 21 41 89 78 79
a3 66 87 56 76 89 90
b1 18 37 46 55 54 63
b2 19 40 50 61 58 76
b3 39 88 88 80 34 39
分组文件：
例如，
#sample group
a1 a
a2 a
a3 a
b1 b
b2 b
b3 b
结果
pcoa.txt
例如
Eigvals 4
4979.38 4105.468 1165.903 0.0000000000004547474
Proportion explained 4
0.4034936 0.3326779 0.09447648 0.00000000000000003684949
Species 0 0
Site 6 4
a1 5.81956407517651 -14.757892747783 -8.99203408229362 0.00000027530206164819
a2 -19.0392179472861 -40.0653857822785 11.3274793700029 0.00000027530206164819
a3 -24.9639390316109 47.0740504660136 5.58657103367427 0.00000027530206164819
b1 -30.4879621365802 -2.63922667263033 -19.314683244903 0.000000275302061648191
b2 15.9998024484013 3.52907723333796 21.3099705972243 0.00000027530206164819
b3 52.6717525918994 6.85937750334027 -9.91730367370479 0.000000275302061648191
Biplot 0 0
Site constraints 0 0
