Noi/NOTES/2012-4-26: Difference between revisions
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Total single SNP 195+109 = 304 | Total single SNP 195+109 = 304 | ||
* Separate the CpG-SNP association based on the distance between CpG and SNP | * Separate the CpG-SNP association based on the distance between CpG and SNP | ||
** Note: Dr. Zhang suggested to break down the CpG-SNP distance with equal length | |||
sed s'/:/\t/g' 10%FDR_2MB_mQTL-noSNP > 10%FDR_2MB_mQTL-noSNP_split_pos | sed s'/:/\t/g' 10%FDR_2MB_mQTL-noSNP > 10%FDR_2MB_mQTL-noSNP_split_pos | ||
Run sh print_distance.sh | Run sh print_distance.sh |
Revision as of 22:38, 26 April 2012
- Link to calendar: [[1]]
- Previous analysis of mQTL on UCLA data set: http://genome-tech.ucsd.edu/LabNotes/index.php/Noi/NOTES/2012-4-11
- Continued from: http://genome-tech.ucsd.edu/LabNotes/index.php/Noi/NOTES/2012-4-21
mQTL analysis on UCLA-SZ data set (no CpG-SNP)
- Details will be filled later
- Filter out SNP from methylMatrix (Note: the sample IDs were modified to be compatible with tfam file and plink)
./remove_snps.pl ./UCLA-4batches_methyl_min76_minSTD0.1-edit /t4T/GenomeDB/HsGenome/snp134_snv.txt > UCLA-4batches_methyl-noSNP_min76_minSTD0.1
61664 UCLA-4batches_methyl-noSNP_min76_minSTD0.1
- Split the methylMatrix in to 10,000 CpG sites each
split -10000 UCLA-4batches_methyl-noSNP_min76_minSTD0.1 UCLA_noSNP_ 10000 UCLA_noSNP_aa 10001 UCLA_noSNP_ab 10001 UCLA_noSNP_ac 10001 UCLA_noSNP_ad 10001 UCLA_noSNP_ae 10001 UCLA_noSNP_af 1666 UCLA_noSNP_ag
- Run mQTL (no CpG-SNP)
nohup ../mQTL_2MB_plink_allP.pl ../UCLA.hg19SNP ../UCLA_noSNP_aa > 2MB_noNSP_aa nohup ../mQTL_2MB_plink_allP.pl ../UCLA.hg19SNP ../UCLA_noSNP_ab > 2MB_noNSP_ab nohup ../mQTL_2MB_plink_allP.pl ../UCLA.hg19SNP ../UCLA_noSNP_ac > 2MB_noNSP_ac nohup ../mQTL_2MB_plink_allP.pl ../UCLA.hg19SNP ../UCLA_noSNP_ad > 2MB_noNSP_ad nohup ../mQTL_2MB_plink_allP.pl ../UCLA.hg19SNP ../UCLA_noSNP_ae > 2MB_noNSP_ae nohup ../mQTL_2MB_plink_allP.pl ../UCLA.hg19SNP ../UCLA_noSNP_af > 2MB_noNSP_af nohup ../mQTL_2MB_plink_allP.pl ../UCLA.hg19SNP ../UCLA_noSNP_ag > 2MB_noNSP_ag
- Concatenate the out put files to the same file
cat mQTL_noSNP_a*/2MB_noNSP_a* > 2MB_mQTL-noSNP_rawoutput awk '{if ($1 ~ /chr/) print $0}' 2MB_mQTL-noSNP_rawoutput > 2MB_mQTL-noSNP_output
- Number of test
433,947 2MB_mQTL-noSNP_output
- Sort out adj. p-val and count the number of significant associated CpG-SNP roughly at different p-value
sort column7 (adj p_val) sort -g -k7 2MB_mQTL-noSNP_output | awk '{if ($7<=0.05) print $0}' | wc -l --> 6,418 sort -g -k7 2MB_mQTL-noSNP_output | awk '{if ($7<=0.01) print $0}' | wc -l --> 2,292 sort -g -k7 2MB_mQTL-noSNP_output | awk '{if ($7<=0.001) print $0}' | wc -l --> 1,026 sort -g -k7 2MB_mQTL-noSNP_output | awk '{if ($7<=0.0001) print $0}' | wc -l --> 698 sort -g -k7 2MB_mQTL-noSNP_output | awk '{if ($7<=0.00001) print $0}' | wc -l --> 526
- Print out the site at min p-value 0.05 before multiple test correction
sort -g -k7 2MB_mQTL-noSNP_output | awk '{if ($7<=0.05) print $0}' > sorted_2MB_mQTL-noSNP_minPVal0.05.txt 6418 sorted_2MB_mQTL-noSNP_minPVal0.05.txt
- Concatenate QVal to the mQTL file
paste -d"\t" sorted_2MB_mQTL-noSNP_minPVal0.05.txt sorted_2MB_mQTL-noSNP_QVal.txt.txt > sorted_2MB_mQTL-noSNP_minPVal0.05_QVal.txt.txt awk '{if ($8 <=0.1) print $0}' sorted_2MB_mQTL-noSNP_minPVal0.05_QVal.txt.txt > 10%FDR_2MB_mQTL-noSNP 741 10%FDR_2MB_mQTL-noSNP p-value cut off: 0.0001636 or 1.636E-4 *Look at # of associated CpG
awk '{print $1}' 10%FDR_2MB_mQTL-noSNP | sort | uniq -u | wc -l 295
awk '{print $1}' 10%FDR_2MB_mQTL-noSNP | sort | uniq -d | wc -l 121 294+121X = 741 --> X ~ (741-295)/121 ~3.69 this show >1 CpGs associated with the same SNP Total single CpG: 294+121 = 415 *Look at # of associated SNP awk '{print $2}' 10%FDR_2MB_mQTL-noSNP | sort | uniq -u | wc -l --> 195 (subtract header line) awk '{print $2}' 10%FDR_2MB_mQTL-noSNP | sort | uniq -d | wc -l --> 109 195+109Y = 741 --> Y ~ (741-195)/109 ~ 5 this also suggest >1 SNP associated with the same CpG Total single SNP 195+109 = 304
- Separate the CpG-SNP association based on the distance between CpG and SNP
- Note: Dr. Zhang suggested to break down the CpG-SNP distance with equal length
sed s'/:/\t/g' 10%FDR_2MB_mQTL-noSNP > 10%FDR_2MB_mQTL-noSNP_split_pos Run sh print_distance.sh
- Note again: P-value of 10%FDR is p <= 1.636E−4
Associated CpG-SNP distance | Number of assiciated CpG-SNP | % |
10%FDR_10kb | 378 | 50.94% |
10%FDR_10-20kb | 27 | 3.64% |
10%FDR_20-30kb | 21 | 2.83% |
10%FDR_30-40kb | 36 | 4.85% |
10%FDR_40-50kb | 2 | 0.27% |
10%FDR_50kb-2Mb | 278 | 37.47% |
Total in 2Mb | 742 |
Associated CpG-SNP distance | Number of assiciated CpG-SNP | % |
minpval0.05_10kb | 862 | 13.43% |
minpval0.05_10-20kb | 124 | 1.93% |
minpval0.05_20-30kb | 133 | 2.07% |
minpval0.05_30-40kb | 108 | 1.68% |
minpval0.05_40-50kb | 75 | 1.17% |
minpval0.05_50kb-2Mb | 5,116 | 79.71% |
Total in 2Mb | 6,418 |
- Get sequences for manhattan plots
Run get_manht_seq.sh