Kun:LabNotes/MONOD/2015-7-16: Difference between revisions
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./[[Media:get_small_insert_count_matrix_2015-7-16.txt|get_small_insert_count_matrix.pl]] > [[Media:150721_MiSeq_small_insert_count_matrix.txt|150721_MiSeq_small_insert_count_matrix.txt]] | ./[[Media:get_small_insert_count_matrix_2015-7-16.txt|get_small_insert_count_matrix.pl]] > [[Media:150721_MiSeq_small_insert_count_matrix.txt|150721_MiSeq_small_insert_count_matrix.txt]] | ||
*I then take the top 100 probes with the most target-independent circularization events, and did the clustering with R. | *I then take the top 100 probes with the most target-independent circularization events, and did the clustering with R. | ||
x=read.table("150721_MiSeq_small_insert_count_matrix_top100.txt",header=TRUE,row.names=1); | x=read.table("[[Media:150721_MiSeq_small_insert_count_matrix_top100.txt|150721_MiSeq_small_insert_count_matrix_top100.txt]]",header=TRUE,row.names=1); | ||
library(gplots) | library(gplots) | ||
heatmap.2(as.matrix(log10(x+1)),scale="none", key=T, symkey=F,density.info="none",trace="none",dendrogram="both",Rowv=TRUE,Colv=TRUE, cexCol=0.6, cexRow=0.3) | |||
[[Media:150721_MiSeq_small_insert_count_top100_heatmap.pdf|Hi-Res PDF]] | [[Media:150721_MiSeq_small_insert_count_top100_heatmap.pdf|Hi-Res PDF]] | ||
[[Image:150721_MiSeq_small_insert_count_top100_heatmap.png|500px]] | [[Image:150721_MiSeq_small_insert_count_top100_heatmap.png|500px]] | ||
*Observations: | |||
**BSPP capture from gDNA or fragmented DNA is cleaner than from WGBS libraries. | |||
**The mean counts for BSPP and those for WGBS-BSPP are still correlated, especially after taking log transformation. | |||
**The top 12 probes represent 70% of the target-independent circularization events from gDNA, and 46% from WGBS libraries. Design suppressor oligos for these probes: | |||
{| {{table}} | |||
| align="center" style="background:#f0f0f0;"|'''probe_id''' | |||
| align="center" style="background:#f0f0f0;"|'''Mean(BSPP)''' | |||
| align="center" style="background:#f0f0f0;"|'''H1''' | |||
| align="center" style="background:#f0f0f0;"|'''H1_Tm''' | |||
| align="center" style="background:#f0f0f0;"|'''H2''' | |||
| align="center" style="background:#f0f0f0;"|'''H2_Tm''' | |||
| align="center" style="background:#f0f0f0;"|'''Suppressor_H2''' | |||
|- | |||
| chr14:75516400c_2568|| 227.88 ||AGAGTTGAGTAAAGGTCGGGTG||62||TCGAGATTAGTTTGATTAATATGGAGAA||59||TCAGGATACACACTACCCTCGAGATTAGTTTGATTAATATGGAGAA | |||
|- | |||
| chr12:111618822w_195|| 146.00 ||AAATTATTTGATTGAAATAATTAGGCGG||58||TGTTAGAGGCGGTTTGTGTATT||60||TCAGGATACACACTACCCTGTTAGAGGCGGTTTGTGTATT | |||
|- | |||
| chr3:50352990c_471|| 36.38 ||AATTAGTCGGGTATGGTGGTGTTTGTTT||65||TGGAGGTTGTAGTGAGTTAAGA||59||TCAGGATACACACTACCCTGGAGGTTGTAGTGAGTTAAGA | |||
|- | |||
| chr14:75516400c_972|| 29.88 ||GGGAGGATTATTTGAGTTTAGGAGTT||61||AAATTAGTTAGGTATGGTGGCGAG||61||TCAGGATACACACTACCCAAATTAGTTAGGTATGGTGGCGAG | |||
|- | |||
| chr13:114909082c_105|| 28.38 ||TATTGTTATATGGTGCGTGGTTGTATTT||62||TGTTATGTGGTGCGTGATTGTA||61||TCAGGATACACACTACCCTGTTATGTGGTGCGTGATTGTA | |||
|- | |||
| chr2:48013200w_1241|| 21.50 ||TTTGGGAGATTGAGATGGGAGGAT||64||TTTAGTTTGGGTGGTAGAGTTAGATT||60||TCAGGATACACACTACCCTTTAGTTTGGGTGGTAGAGTTAGATT | |||
|- | |||
| chr20:32378088c_130|| 17.63 ||TTATTTATAGGATTATAGGTTAGGCGT||58||TTATTTGAGGTTAGGAGTTCGAT||58||TCAGGATACACACTACCCTTATTTGAGGTTAGGAGTTCGAT | |||
|- | |||
| chr3:50352990c_186|| 14.75 ||TTTAGTTTGGGTGATAGAGTAAGATTT||59||GAGAAAGGAGTTGTGGTTTGTTT||60||TCAGGATACACACTACCCGAGAAAGGAGTTGTGGTTTGTTT | |||
|- | |||
| chr6:137242190w_106|| 14.13 ||TGAATTTAGAATAAAGAGTTATCGAAGT||58||TTTGTGGTGTAAAGGTGTGAAT||59||TCAGGATACACACTACCCTTTGTGGTGTAAAGGTGTGAAT | |||
|- | |||
| chr5:132161518c_356|| 14.00 ||GTATTTATTTGCGTAGTTATGGAGGT||60||TGGATTTGTGGTATTTGTTTATGC||59||TCAGGATACACACTACCCTGGATTTGTGGTATTTGTTTATGC | |||
|- | |||
| chr7:6047900w_2500|| 13.75 ||TTATTATGTTGGTTAGGTTGATTTCG||58||ATTATAGGTGTGAGTTATCGTGTT||58||TCAGGATACACACTACCCATTATAGGTGTGAGTTATCGTGTT | |||
|- | |||
| chr14:105119324c_429|| 10.00 ||AGGTTTGGATATATTAGGTTCGTT||58||GTTTGGATATATTAGGTTCGTTTAGT||58||TCAGGATACACACTACCCGTTTGGATATATTAGGTTCGTTTAGT | |||
|- | |||
| | |||
|} |
Latest revision as of 06:10, 24 July 2015
MONOD V6 (aka MONOD June2015)[edit]
Probe Design[edit]
- Target selection:
1. MONOD v1/v3 efficient targets 2. BluePrint efficient targets 3. Illumina/USC 1000 CRC targets 4. Hand curated colon cancer methylation markers 5. Hypermethylated genes from Hyen & Esteller NRG 2012 (Table 1&3) 6. Commonly methylated genes from Ciriello et al NG 2013 (Figure 1C) 7. Guo TCGA top 75 sites 8. Guo TCGA NSCLC 5 sites 9. Dana's gene list (BRCA1, MLH and related genes)
- Design log: (Genome-miner: /home/kunzhang/CpgMIP/MONOD/June2015_probe_design)
sort -k 1,1 -k 2,2n MONOD_June2015_all_targets_bed.txt | awk '{print $1"\t"$2"\t"$3}' | /home/kunzhang/softwares/bedtools-2.20/bin/bedtools merge -d 40 -i - > MONOD_June2015_all_targets_merged_bed.txt
awk '{print $1":"$2"w\t"$1"\t"$2"\t"$3"\t+"'} MONOD_June2015_all_targets_merged_bed.txt > MONOD_June2015_all_targets_merged_ppDesigner.in awk '{print $1":"$2"c\t"$1"\t"$2"\t"$3"\t-"'} MONOD_June2015_all_targets_merged_bed.txt >> MONOD_June2015_all_targets_merged_ppDesigner.in split -l 1000 MONOD_June2015_all_targets_merged_ppDesigner.in MONOD_June2015_all_targets_merged_ppDesigner.in.
sed 's/aa/ab/' < jobFile_June2015.pl > jobFile_June2015_ab.pl sed 's/aa/ac/' < jobFile_June2015.pl > jobFile_June2015_ac.pl sed 's/aa/ad/' < jobFile_June2015.pl > jobFile_June2015_ad.pl sed 's/aa/ae/' < jobFile_June2015.pl > jobFile_June2015_ae.pl sed 's/aa/af/' < jobFile_June2015.pl > jobFile_June2015_af.pl sed 's/aa/ag/' < jobFile_June2015.pl > jobFile_June2015_ag.pl sed 's/aa/ah/' < jobFile_June2015.pl > jobFile_June2015_ah.pl
/home/kunzhang/softwares/ppDesigner_Kun_version/src/ppDesigner.pl jobFile_June2015.pl > June2015_probes.aa.txt & /home/kunzhang/softwares/ppDesigner_Kun_version/src/ppDesigner.pl jobFile_June2015_ab.pl > June2015_probes.ab.txt & /home/kunzhang/softwares/ppDesigner_Kun_version/src/ppDesigner.pl jobFile_June2015_ac.pl > June2015_probes.ac.txt & /home/kunzhang/softwares/ppDesigner_Kun_version/src/ppDesigner.pl jobFile_June2015_ad.pl > June2015_probes.ad.txt & /home/kunzhang/softwares/ppDesigner_Kun_version/src/ppDesigner.pl jobFile_June2015_ae.pl > June2015_probes.ae.txt & /home/kunzhang/softwares/ppDesigner_Kun_version/src/ppDesigner.pl jobFile_June2015_af.pl > June2015_probes.af.txt & /home/kunzhang/softwares/ppDesigner_Kun_version/src/ppDesigner.pl jobFile_June2015_ag.pl > June2015_probes.ag.txt & /home/kunzhang/softwares/ppDesigner_Kun_version/src/ppDesigner.pl jobFile_June2015_ah.pl > June2015_probes.ah.txt &
cat June*.txt > MONOD_June2015_all_targets_probeInfo.txt grep probes MONOD_June2015_all_targets_probeInfo.txt | awk '{print $1}' > MONOD_June2015_1st_design_failed_targets.txt match_column.pl MONOD_June2015_1st_design_failed_targets.txt MONOD_June2015_all_targets_merged_ppDesigner.in 1 > MONOD_June2015_all_targets_merged_ppDesigner_2nd.in # allow for up to 2 CpG sites per arm /home/kunzhang/softwares/ppDesigner_Kun_version/src/ppDesigner.pl jobFile_June2015_2nd.pl > June2015_probes_2nd.txt &
- Assembled with the V6 amplification adaptors.
- ProbeInfo file: Media:MONOD_June2015_all_targets_probeInfo.txt
- Oligo sequences: Media:MONOD_Jun2015_sequence.txt
Experiments[edit]
First test[edit]
- Dinh did the first test:Dinh/Dinh_2015/NOTES/2015-6-25.
- The sequencing data are in genome-miner: /media/LTS_33T/SeqStore2/150721_MiSeq
- I did the checking for target-independent circularization, by taking 100,
#in the working directory: /home/kunzhang/CpgMIP/MONOD/Data/150721_MiSeq ./batch_map_N_parse.pl ./get_small_insert_count_matrix.pl > 150721_MiSeq_small_insert_count_matrix.txt
- I then take the top 100 probes with the most target-independent circularization events, and did the clustering with R.
x=read.table("150721_MiSeq_small_insert_count_matrix_top100.txt",header=TRUE,row.names=1); library(gplots) heatmap.2(as.matrix(log10(x+1)),scale="none", key=T, symkey=F,density.info="none",trace="none",dendrogram="both",Rowv=TRUE,Colv=TRUE, cexCol=0.6, cexRow=0.3)
Hi-Res PDF File:150721 MiSeq small insert count top100 heatmap.png
- Observations:
- BSPP capture from gDNA or fragmented DNA is cleaner than from WGBS libraries.
- The mean counts for BSPP and those for WGBS-BSPP are still correlated, especially after taking log transformation.
- The top 12 probes represent 70% of the target-independent circularization events from gDNA, and 46% from WGBS libraries. Design suppressor oligos for these probes:
probe_id | Mean(BSPP) | H1 | H1_Tm | H2 | H2_Tm | Suppressor_H2 |
chr14:75516400c_2568 | 227.88 | AGAGTTGAGTAAAGGTCGGGTG | 62 | TCGAGATTAGTTTGATTAATATGGAGAA | 59 | TCAGGATACACACTACCCTCGAGATTAGTTTGATTAATATGGAGAA |
chr12:111618822w_195 | 146.00 | AAATTATTTGATTGAAATAATTAGGCGG | 58 | TGTTAGAGGCGGTTTGTGTATT | 60 | TCAGGATACACACTACCCTGTTAGAGGCGGTTTGTGTATT |
chr3:50352990c_471 | 36.38 | AATTAGTCGGGTATGGTGGTGTTTGTTT | 65 | TGGAGGTTGTAGTGAGTTAAGA | 59 | TCAGGATACACACTACCCTGGAGGTTGTAGTGAGTTAAGA |
chr14:75516400c_972 | 29.88 | GGGAGGATTATTTGAGTTTAGGAGTT | 61 | AAATTAGTTAGGTATGGTGGCGAG | 61 | TCAGGATACACACTACCCAAATTAGTTAGGTATGGTGGCGAG |
chr13:114909082c_105 | 28.38 | TATTGTTATATGGTGCGTGGTTGTATTT | 62 | TGTTATGTGGTGCGTGATTGTA | 61 | TCAGGATACACACTACCCTGTTATGTGGTGCGTGATTGTA |
chr2:48013200w_1241 | 21.50 | TTTGGGAGATTGAGATGGGAGGAT | 64 | TTTAGTTTGGGTGGTAGAGTTAGATT | 60 | TCAGGATACACACTACCCTTTAGTTTGGGTGGTAGAGTTAGATT |
chr20:32378088c_130 | 17.63 | TTATTTATAGGATTATAGGTTAGGCGT | 58 | TTATTTGAGGTTAGGAGTTCGAT | 58 | TCAGGATACACACTACCCTTATTTGAGGTTAGGAGTTCGAT |
chr3:50352990c_186 | 14.75 | TTTAGTTTGGGTGATAGAGTAAGATTT | 59 | GAGAAAGGAGTTGTGGTTTGTTT | 60 | TCAGGATACACACTACCCGAGAAAGGAGTTGTGGTTTGTTT |
chr6:137242190w_106 | 14.13 | TGAATTTAGAATAAAGAGTTATCGAAGT | 58 | TTTGTGGTGTAAAGGTGTGAAT | 59 | TCAGGATACACACTACCCTTTGTGGTGTAAAGGTGTGAAT |
chr5:132161518c_356 | 14.00 | GTATTTATTTGCGTAGTTATGGAGGT | 60 | TGGATTTGTGGTATTTGTTTATGC | 59 | TCAGGATACACACTACCCTGGATTTGTGGTATTTGTTTATGC |
chr7:6047900w_2500 | 13.75 | TTATTATGTTGGTTAGGTTGATTTCG | 58 | ATTATAGGTGTGAGTTATCGTGTT | 58 | TCAGGATACACACTACCCATTATAGGTGTGAGTTATCGTGTT |
chr14:105119324c_429 | 10.00 | AGGTTTGGATATATTAGGTTCGTT | 58 | GTTTGGATATATTAGGTTCGTTTAGT | 58 | TCAGGATACACACTACCCGTTTGGATATATTAGGTTCGTTTAGT |