Kun:LabNotes/ExonomeSeq/2009-4-1: Difference between revisions

From ZhangLabWiki
Jump to navigation Jump to search
 
(6 intermediate revisions by the same user not shown)
Line 6: Line 6:
==Questions to answer==
==Questions to answer==
===Was the library construction successful?===
===Was the library construction successful?===
It seems pretty good. Here is the distribution of reads that mapped to the same location.
[[Image:2009-03-30-clonality_check.png|500px]]
===What is the level of representation bias?===
===What is the level of representation bias?===
It is slightly higher than the bias in end-sequencing analysis, but not too much. The library construction could be improved. Library-free sequencing would be better.
  [[Image:2009-03-30-AbsoluteCoverageDist.png|300px]] [[Image:2009-03-30-RelativeCoverageDist.png|300px]]
===What is the fraction of on-target reads?===
===What is the fraction of on-target reads?===
*Read mapping using Soap2 with the default setting.
**19,132,747 total reads.
**15,217,219 mapped.
*I used this [[Media:seqCoverage.txt |Perl script]] to generate the following statistics:
                        Genome covered(bps)  Sequenced(bps)     
    Mapped reads: 44,333,324       608,688,760
    On-target reads: 15,064,164       499,303,049 (33x)  82%
    Near-target reads: 4,005,655       93,306,387  (23x)  15%
===What is the fraction of reads that came from linker sequences or capturing arms?===
===What is the fraction of reads that came from linker sequences or capturing arms?===
===How many SNPs were identified? What is the false positive rate?===
===How many SNPs were identified? What is the false positive rate?===
*I've tried both Maq and Soap on either the full genome template or the captured targets only. SNP calling was based on the minimal sequencing coverage of 8x and the minimal quality score of 30.
                  Full genome      Targets only
      Maq        10,655              10,202
      SOAP                            10,698
    [[Image:Comparison_of_SNP_calling_strategies.png|400px]]

Latest revision as of 21:54, 12 May 2009

Data analysis of shotgun sequencing data[edit]

  • Two libraries were made by Alice. The capturing reactions were done with Jan09 #1-3 probe set (150k) on PGP1.
  • s3 (PGP1-CTRL): 9707995 raw reads, 40bp, 7655774 (79%) mappable (SOAP2 to hg18)
  • s4 (PGP1-Shaked): 9424752 raw reads, 40bp, 7561445 (80%) mappable (SOAP2 to hg18)

Questions to answer[edit]

Was the library construction successful?[edit]

It seems pretty good. Here is the distribution of reads that mapped to the same location. File:2009-03-30-clonality check.png

What is the level of representation bias?[edit]

It is slightly higher than the bias in end-sequencing analysis, but not too much. The library construction could be improved. Library-free sequencing would be better.

 File:2009-03-30-AbsoluteCoverageDist.png File:2009-03-30-RelativeCoverageDist.png

What is the fraction of on-target reads?[edit]

  • Read mapping using Soap2 with the default setting.
    • 19,132,747 total reads.
    • 15,217,219 mapped.
  • I used this Perl script to generate the following statistics:
                       Genome covered(bps)   Sequenced(bps)      
   Mapped reads:	44,333,324	      608,688,760
   On-target reads:	15,064,164	      499,303,049 (33x)  82%
   Near-target	reads:	 4,005,655	      93,306,387  (23x)  15%

What is the fraction of reads that came from linker sequences or capturing arms?[edit]

How many SNPs were identified? What is the false positive rate?[edit]

  • I've tried both Maq and Soap on either the full genome template or the captured targets only. SNP calling was based on the minimal sequencing coverage of 8x and the minimal quality score of 30.
                 Full genome       Targets only
      Maq         10,655              10,202
      SOAP                            10,698
   File:Comparison of SNP calling strategies.png