Name
Title | ||
|---|---|---|
An Approach for Metabonomics Data Analysis Based on Orthogonal Signal Correction Partical Least Square Discriminate Analysis |
Abstract | ||
|---|---|---|
Datasets resulting from metabolomics or metabolic profiling experiments are becoming increasingly complex, which is hard to summarize and virsualize without appropriate tools. The use of chemometric tools, such as orthogonal signal correction(OSC), principal component analysis (PCA), Partial least squares to latent structure discriminant analysis (PLS-DA), make the data dimensionality reduction and interpretation much easier. Here we showed an system method based on PCA, OSC-PLS-DA for metabonomic data analysis; Furthermore, U-plot, as a visualized tool, combined with independent samples T test, were used for the biomarkers discovery. As an example, dataset from RZ water extract administrated rats urine collected by LC/MS/MS was used to demonstrate this method. As a result, U-plot based on OSC-PLS-DA was proved to be an effective, time saving tool for data interpretation and biomarkers discovery. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/APWCS.2010.90 | APWCS |
Keywords | Field | DocType |
chemometric tool,latent structure discriminant analysis,least square discriminate analysis,metabonomic data analysis,partial least squares to latent structure discriminant analysis (pls-da),data dimensionality reduction,orthogonal signal correction partical,visualized tool,biomarkers discovery,data analysis,square discriminate analysis,-principal component analysis (pca),system method,biology computing,metabonomics data analysis,appropriate tool,orthogonal signal correction (osc),metabolic profiling experiments,u-plot,genetic algorithms,orthogonal signal correction,data interpretation,partial least squares,rats urine,principal component analysis,chemometric tools,biomarkers,system testing,metabolomics,data visualization,signal analysis,discriminant analysis,data models,independent component analysis,data mining,least square | Least squares,Data modeling,Pattern recognition,Computer science,Profiling (computer programming),Partial least squares regression,Orthogonal signal correction,Metabolomics,Artificial intelligence,Linear discriminant analysis,Principal component analysis | Conference |
ISBN | Citations | PageRank |
978-1-4244-6468-5 | 0 | 0.34 |
References | Authors | |
0 | 7 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Guoliang Xu | 1 | 9 | 2.08 |
| Bingtao Li | 2 | 0 | 0.34 |
| Qiyun Zhang | 3 | 19 | 1.82 |
| Xilan Tang | 4 | 0 | 0.34 |
| Hongning Liu | 5 | 0 | 1.01 |
| Bing Nie | 6 | 0 | 0.34 |
| Riyue Yu | 7 | 1 | 1.03 |