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==Second analysis of BSPP data from Geographic Astrophy (GA) patients== *This is the continuation of the first analysis did on [[Kun:LabNotes/CpgSeq/2011-10-14|2011-10-14]]. *The purpose of this analysis is to use the UCLA SZ samples as the controls to test the accuracy of classification based on methylation markers. *Noi did the mapping and generated BED files for both data sets. [[Noi/NOTES/2012-1-24|UCLA SZ data]]; [[Noi/NOTES/2012-2-1|UCSD GA data]] *I generated the methylation matrix by myself using my allBED2Matrix.pl script, because there is a 1bp difference in CpG positions between my script and Dinh's version. **For the GA samples, I required that there are at least 58 methylation values at each CpG site, and the standard deviation is at least 0.1. **For the UCLA SZ samples, I required at least 50 methylation values, but no threshold for standard deviation, because the informative CpG sites identified from the GA samples might not be variable in the SZ samples. *I made one modification in the [[media:GA_methylation_MRMR_prep_v2.txt|GA_methylation_MRMR_prep.pl]], so that all candidate CpG sites have no missing value. ./GA_methylation_MRMR_prep.pl Feb2012/GA_goodqual_min58_minSTD0.1_methylMatrix_noSNP.txt > Feb2012/GA_goodqual_min58_minSTD0.1_methylMatrix_noSNP_MRMR_input.csv & ~kunzhang/softwares/mrmr_c_src/mrmr -i GA_goodqual_min58_minSTD0.1_methylMatrix_noSNP_MRMR_input.csv > GA_goodqual_min58_minSTD0.1_methylMatrix_noSNP_MRMR_output.txt *I took the top 50 MaxRel features, and extract the methylation values on these sites from the UCLA SZ data set. ../extract_N_prep_matrix.pl GA_goodqual_methyl_min58_minSTD0.1.noSNP.50_marker_list UCLA-4batches_all_methylMatrix.txt *I then manually removed the CpG sites (or samples) that have missing values, then combined the UCLA SZ data and UCSD GA data on 35 CpG sites: [[Media:UCLA-SZ-UCSD_GA_35_marker.methylMatrix.txt|UCLA-SZ-UCSD_GA_35_marker.methylMatrix]]. *PCA analysis was performed on this combined matrix. Then I plotted all 166 samples based on the first two principal components. Green: GA controls; Red: GA cases; Blue: SZ samples (unrelated controls) [[Image:PCA_classification_35_cpg_sites.png|1000px]] *Conclusion: Clearly the SZ samples cluster closely to the GA controls than the GA cases, which is a good indication that these methylation markers (as well as this strategy) could be valid.
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