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:

  1. Haplotype file: xxx.methylHap.txt
    1. One molecule per line;
    2. target_id, offset1, methylotype1, offset2, methylotype2...
  2. Methylation level file, average methylation level per site: xxx.methylFreq.txt
  3. 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.