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==Data analysis: re-defining bins based on methylation haplotype blocks== *I have previously defined a set of methylation LD blocks based on the N37 and whole-blood WGBS data, plus tumor RRBS data:[[Kun:LabNotes/MONOD/2015-3-11]]. *Since several WGBS data sets have been published lately, I decided to repeat this using all WGBS data, in order to be as unbiased as possible. *The list of WGBS data sets included are (Dinh did all the mapping and gave me the mapped bam files): **Whole blood WGBS data (REF); **Our internal N37 WGBS data (ten tissues): /media/LTS_33T/WGBS_LTS33/Hg19/Noi_N37_WGBS/BAMfiles **WGBS data from H1 ESCs and differentiated cells (REF): /media/LTS_33T/WGBS_LTS33/Hg19/Xie2013/Re-map/BAMfiles **WGBS data from human adult tissues (Salk, REF): /media/TmpStore2/Dinh_Store2/Tissues_WGBS_Ecker/BAMfiles **WGBS data from a cancer cell line and a colon cancer tumor tissue (REF): /media/TmpStore2/Dinh_Store2/Tumor_WGBS/BAMfiles *I still use the same "mappable bins" to generate the initial hapInfo files for mld_block partitioning. This was done on TSCC since there are so many files to process. **Transfer bam files to TSCC. **Create a "sampleInfo" file to each data set. **Create job files and submit them to the queue. /home/k4zhang/my_oasis_tscc/MONOD/batch_bam2hapInfo2.pl [[Media:H1ESC_WGBS_sampleInfo_mappable_bins.txt]] /home/k4zhang/my_oasis_tscc/MONOD/batch_bam2hapInfo2.pl [[Media:Ecker-Tissue_WGBS_sampleInfo_mappable_bins.txt]] /home/k4zhang/my_oasis_tscc/MONOD/batch_bam2hapInfo2.pl [[Media:N37_10_tissue_pool_WGBS_sampleInfo_mappable_bins.txt]] /home/k4zhang/my_oasis_tscc/MONOD/batch_bam2hapInfo2.pl [[Media:whole_blood_WGBS_sampleInfo_mappable_bins.txt]] /home/k4zhang/my_oasis_tscc/MONOD/batch_bam2hapInfo2.pl [[Media:tumor_WGBS_sampleInfo_mappable_bins.txt]] **Transfer all hapInfo files to genome-miner, merge and call mld_blocks. ./merge_all_WGBS_hapInfo_by_chr.pl {| {{table}} | align="center" style="background:#f0f0f0;"|'''Chromosome''' | align="center" style="background:#f0f0f0;"|'''Total_block_size(bp)''' | align="center" style="background:#f0f0f0;"|'''Average_block_size(bp)''' | align="center" style="background:#f0f0f0;"|'''Number_of_blocks''' |- | chr1|| 1,313,397 || 93 || 14,039 |- | chr2|| 1,036,535 || 95 || 10,865 |- | chr3|| 837,635 || 101 || 8,221 |- | chr4|| 617,761 || 96 || 6,424 |- | chr5|| 702,048 || 96 || 7,269 |- | chr6|| 818,849 || 98 || 8,281 |- | chr7|| 721,352 || 91 || 7,915 |- | chr8|| 619,684 || 96 || 6,405 |- | chr9|| 582,178 || 91 || 6,353 |- | chr10|| 679,991 || 91 || 7,413 |- | chr11|| 755,885 || 96 || 7,870 |- | chr12|| 708,022 || 98 || 7,176 |- | chr13|| 329,397 || 95 || 3,459 |- | chr14|| 476,826 || 97 || 4,881 |- | chr15|| 477,637 || 95 || 5,008 |- | chr16|| 635,834 || 99 || 6,386 |- | chr17|| 798,337 || 92 || 8,605 |- | chr18|| 263,857 || 89 || 2,958 |- | chr19|| 800,571 || 92 || 8,620 |- | chr20|| 429,997 || 95 || 4,493 |- | chr21|| 158,893 || 87 || 1,818 |- | chr22|| 306,308 || 89 || 3,429 |- | Total|| 14,070,994 |||| 147,888 |- | |} **Transfer the bed files to TSCC, and generate all hapInfo files for the mld_blocks. **Transfer all hapInfo files for the mld_blocks back to genome-miner, create the methHap_load_matrix. ***All WGBS data: /home/kunzhang/CpgMIP/MONOD/Data/WGBS_data/mld_block_hapInfo_July2015/All_chromosomes_combined/WGBS_methHap_load_matrix_July2015.txt ***All RRBS data:/home/kunzhang/CpgMIP/MONOD/Data/1407-combined_RRBS/mld_blocks_hapInfo_July2015/RRBS_methHap_load_matrix_July2015.txt ***All WGBS-SeqCap data: /home/kunzhang/CpgMIP/MONOD/Data/150209_SN216/SeqCap/mld_blocks_July2015/WGBS_SeqCap_methHap_load_matrix_July2015.txt
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