Kun:LabNotes/CpgSeq/2008-5-23: Difference between revisions
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-v 5 -e 10000 -c 0 -f 8 -r 0 -s 9 | -v 5 -e 10000 -c 0 -f 8 -r 0 -s 9 | ||
*To find out whether the 2% unmappable reads were due to multiple mapping positions or too many C:T mismatches, I generated another set of mock reads from completely methylated sequences (so that there is no C:T mismatch). It turned out that 100% reads were successfully mapped to the targets, which means the mapping strategy is bias towards methylated sequence. | *To find out whether the 2% unmappable reads were due to multiple mapping positions or too many C:T mismatches, I generated another set of mock reads from completely methylated sequences (so that there is no C:T mismatch). It turned out that 100% reads were successfully mapped to the targets, which means the mapping strategy is bias towards methylated sequence. | ||
*I generated a third set of mock reads from completely unmethylated sequences, and performed the mapping with the same parameters. Only 85% reads were mappable. | *I generated a third set of mock reads from completely unmethylated sequences, and performed the mapping with the same parameters. Only 85% reads were mappable. In contrast, if I replace all CGs with TGs in the target sequences, 100% reads were mappable. | ||
*I think the best mapping strategy is to map the reads to the completely methylated targets, and to the completely unmethylated targets, then take the union of the mapping results. | *I think the best mapping strategy is to map the reads to the completely methylated targets, and to the completely unmethylated targets, then take the union of the mapping results. |
Revision as of 05:12, 26 May 2008
Informatics
Read mapping
Should generate three files:
- Haplotype file: xxx.methylHap.txt
- One molecule per line;
- target_id, offset1, methylotype1, offset2, methylotype2...
- Methylation level file, average methylation level per site: xxx.methylFreq.txt
- Methylation LD statistics file, all LD statistics: xxx.methylLD.txt
Mock read generation
- 50% methylation at every CpG site;
- No correlation between adjacent CpG;
- Read position is evenly distributed;
- Can generate both single reads and pair-end reads;
- Incorporate an error model for sequencing;
- Should generate one raw read file and one methylHap file.
Perl Script: Media:mockReadsGenV1.txt
- I generated mock reads at 50X coverage (3,414,819 reads). 98% were mapped back to the target sequences with SOAP with the following parameters:
-v 5 -e 10000 -c 0 -f 8 -r 0 -s 9
- To find out whether the 2% unmappable reads were due to multiple mapping positions or too many C:T mismatches, I generated another set of mock reads from completely methylated sequences (so that there is no C:T mismatch). It turned out that 100% reads were successfully mapped to the targets, which means the mapping strategy is bias towards methylated sequence.
- I generated a third set of mock reads from completely unmethylated sequences, and performed the mapping with the same parameters. Only 85% reads were mappable. In contrast, if I replace all CGs with TGs in the target sequences, 100% reads were mappable.
- I think the best mapping strategy is to map the reads to the completely methylated targets, and to the completely unmethylated targets, then take the union of the mapping results.