Noi/NOTES/2012-3-21

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Revision as of 01:31, 22 March 2012 by >Noi
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ASM analysis of UCLA SZ data set

  • After discussing with Dr. Zhang and Dinh about how to identify sequence-dependent ASM, Dr. Zhang suggested to identify the consistency of sequence preference DNA methylation across individual
  • After having more discussion with Dinh, she helped me out to write scripts for sequence-dependent ASM using binomial test and t-test by testing on ASM HAPMAP data (total 12 samples): [[1]]
on genome-miner: /home/nplongth/Noi_scratch/ASM_HAPMAP1362-1454_2012_02_03/DD_SequenceDependentTest
  • I did the same analysis on UCLA SZ data set
on genome-miner: /home/nplongth/Noi_scratch/ASM_UCLA/combined_ASM_UCLA-4batches_2012_01_24
  • Since there were mislabeling of some samples at the beginning from UCLA and after mapping and ASM analysis, and I generated many files. I still kept all labeling the same as original, but made the correction when generated the methylation matrix or other sample_list files for any analysis. Here are the list of samples used in analysis and correction.

Correct data mislabeling in UCLA.SZ data set
Note: --> = change the labeling to
GK0210-001 --> GK0210-002
GK0210-002 --> GK0210-001
GK0050-005a --> GK0277-002
GK0277-002 --> GK0344-004
GK0344-004 --> GK0050-005a

./asmBinomialTest.pl UCLA_MFASM_Qcpg_list.txt > UCLA_SZ_SeqDepTest_Binomial_PVal0.05.txt
I got total 8,510 SNP:CpG sites showing significant ASM using p-value cutoff 0.05. However, when I look closer to the fraction of methylation level, it showed that some significant sites by this test and p-value cutoff have very close methylation level or had the methylation fraction 0 on both alleles. I may try to increasing stringency by lowering the cufoff p-value and observe the resulting methylation fraction.