Kun:LabNotes/MONOD/2014-10-1
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Analysis of BSPP_WGBS data
- For targeted bisulfite sequencing of cfDNA, we decided to first make WGBS libraries to enrich the short cfDNA fragments, then perform BSPP capture on the amplified libraries.
- Noi did one round of experiment on 16 samples, and the libraries were sequenced on multiple HiSeq Rapid Runs.
- Dinh ran the mapping of the 140914_HiSeqRapidRun data, and the results are in /media/Ext12T/DD_Ext12T/MONOD/140914_HiSeqRapidRun/NO_RMDUP.
- To compare with my previous BSPP results, I also did the mapping of 140919_HiSeqRapidRun data in the old way, and keep the results in /home/kunzhang/CpgMIP/MONOD/Data/140919_HiSeqRapidRun/SE150. Note that the same batch of libraries were sequenced in multiple flow cells, so the results can be combined or compared.
Sample id | Input | All mapped reads | On-target reads | On-target rate |
6-T-2 | gDNA | 15,259,826 | 12,294,400 | 80.6% |
6-T-4 | gDNA | 16,834,556 | 15,695,043 | 93.2% |
6-T-3 | gDNA | 15,454,340 | 14,637,901 | 94.7% |
COLO2-03 | WGBS | 13,098,434 | 571,663 | 4.4% |
NORM1-03 | WGBS | 13,383,336 | 649,907 | 4.9% |
cfDNA | WGBS | 9,498,520 | 585,118 | 6.2% |
NORM1-02 | WGBS | 12,839,754 | 853,671 | 6.6% |
6-P-5 | WGBS | 14,116,370 | 1,201,083 | 8.5% |
6-P-4 | WGBS | 10,335,816 | 982,269 | 9.5% |
6-P-2 | WGBS | 9,200,684 | 1,352,128 | 14.7% |
6-P-3 | WGBS | 12,153,832 | 4,051,723 | 33.3% |
NC-30 | WGBS | 9,341,122 | 4,873,918 | 52.2% |
NC-27 | WGBS | 8,709,818 | 5,455,158 | 62.6% |
NC-9 | WGBS | 10,843,616 | 7,406,900 | 68.3% |
NC-6 | WGBS | 18,171,498 | 15,146,583 | 83.4% |
- Clearly there is a hug variability in terms of mapping rates. The libraries from tumor gDNA have the highest mapping rate. Some libraries from plasma WGBS libraries also have decent mapping rates, but six libraries have very low mapping rates.
- Next I looked into absolute probe capturing efficiencies. Since there is the clear difference between gDNA or WGBS libraries as the input, I split the samples into several groups.
- Based on the data from gDNA, the UMI counts per probe are quite consistent across the four samples. Among the most efficient 2884 probes, the average CV is 0.18. Also for 100ng of input DNA, roughly 18,440 probes are usable for quantifying methylation (unique counts >=10).
Efficiency # probes >0.05 27 >0.01 1,158 >0.005 2,884 >0.001 10,704 >0.0005 15,209 >0.0001 24,771 >0 35,272 Total 39,722