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Finding significant features
A naive approach for finding which features in the sample are significant is to assume that each M/Z value is independent and do a two-way t-test.
numPoints = numel(NH_MZ);
h = false(numPoints,1);
p = nan+zeros(numPoints,1);
for count = 1:numPoints
[h(count) p(count)] = ttest2(NH_IN(count,:),OC_IN(count,:),.0001,'both','unequal');
end% h can be used to extract the significant M/Z values
sig_Masses = NH_MZ(find(h));
We can plot the p-values over the spectra
figure(hFig);
plot(NH_MZ,-log(p),'g')
% notice that there are significant regions at high m/z values but low% intensity.
图在附件中了,图中是来自两个样本的质谱图,一个为正正常组的,另一个是疾病组的,疾病组的图中肯定比正常组多出一些峰,我想以上这些程序就是用来找特征峰的,但是我是初学者,那些具体的命令的含义我不太懂,那为做过这方面的,麻烦帮我翻译一下,或是给点建议,该查那些资料来自学呢?
close all; clear DR
We could also use the p-value to extract significant points.
sig_Masses = NH_MZ(find(p<1e-6)); |
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