Athurva Gore/LabNotes/2009-8-17: Difference between revisions

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=Exome Sequencing Project=
=Exome Sequencing Project=
* Text of Dr. Zhang's Email:
* Text of Dr. Zhang's Email:
  I’m sending you a list of NA12878 variants called from ~40 millions high quality reads. I have pretty good feeling about these calls using a simple filter of depth >=8x and SNP quality >=30. Can you please help me to get the following numbers:
  I’m sending you a list of NA12878 variants called from ~40 millions high quality reads. I have pretty good
  (1)    What is the total size of exonic region that were covered by >=8x in this data set? For that you will need the pileup file which is available on genome-tech in my folder: WorkSpace/Exome/Solexa/NA12878/
feeling about these calls using a simple filter of depth >=8x and SNP quality >=30. Can you please help me to  
get the following numbers:
  (1)    What is the total size of exonic region that were covered by >=8x in this data set? For that you will  
need the pileup file which is available on genome-tech in my folder: WorkSpace/Exome/Solexa/NA12878/
  NA12878_061009_061109_080509_081309_40bp_sequence.bowtie.pileup
  NA12878_061009_061109_080509_081309_40bp_sequence.bowtie.pileup
  (2)    How many variants found are within these regions and how many located outside of our target regions (non-specific capture)?
  (2)    How many variants found are within these regions and how many located outside of our target regions  
  (3)    How many SNPs and variants did you see in Hapmap and 1KG data sets, and how consistent our variant calls are compared with the reference data?
      (non-specific capture)?
  (4)    If you remove some apparent false-positives that tends to localize very close to each other (probably due to mapping issues), what the numbers are in (3)?
  (3)    How many SNPs and variants did you see in Hapmap and 1KG data sets, and how consistent our variant  
  (5)    Using 1KG data as reference, what is our false positive rate as the function of the filter we used? This could be plotted as a curve. Also what is the total variants we can call as the function of false-positive rate?
        calls are compared with the reference data?
  We will submit this data set to the exome sequencing program to compare with data generated by two other centers. Ideally we should have these numbers before we submit the data.
  (4)    If you remove some apparent false-positives that tends to localize very close to each other (probably  
        due to mapping issues), what the numbers are in (3)?
  (5)    Using 1KG data as reference, what is our false positive rate as the function of the filter we used?  
        This could be plotted as a curve. Also what is the total variants we can call as the function of false-
        positive rate?
  We will submit this data set to the exome sequencing program to compare with data generated by two other  
centers. Ideally we should have these numbers before we submit the data.
   
   
  Thanks!
  Thanks!

Revision as of 20:55, 17 August 2009

Navigation

Probe Generation

  • DONE
    • KKESH72
    • RPLCACRD
    • CpG-SNP set (with 80 bp gap)
    • FlyDup936
    • A-to-I Probes for Erez and Billy
    • LeeCancer (on opposite strand to target cDNA)
    • LeeXGenes (on opposite strand to target cDNA)
    • ZhangSNP (on opposite strand to target cDNA)
  • CURRENTLY RUNNING:
    • FlyDup901
    • FlyDup5279
  • TO RERUN:
    • TDMR Set (Also check if out-of-memory happens again...maybe run on Miner?)

Exome Sequencing Project

  • Text of Dr. Zhang's Email:
I’m sending you a list of NA12878 variants called from ~40 millions high quality reads. I have pretty good
feeling about these calls using a simple filter of depth >=8x and SNP quality >=30. Can you please help me to 
get the following numbers:
(1)    What is the total size of exonic region that were covered by >=8x in this data set? For that you will 
need the pileup file which is available on genome-tech in my folder: WorkSpace/Exome/Solexa/NA12878/
NA12878_061009_061109_080509_081309_40bp_sequence.bowtie.pileup
(2)    How many variants found are within these regions and how many located outside of our target regions 
      (non-specific capture)?
(3)    How many SNPs and variants did you see in Hapmap and 1KG data sets, and how consistent our variant 
       calls are compared with the reference data?
(4)    If you remove some apparent false-positives that tends to localize very close to each other (probably 
       due to mapping issues), what the numbers are in (3)?
(5)    Using 1KG data as reference, what is our false positive rate as the function of the filter we used? 
       This could be plotted as a curve. Also what is the total variants we can call as the function of false-
       positive rate?
We will submit this data set to the exome sequencing program to compare with data generated by two other 
centers. Ideally we should have these numbers before we submit the data.

Thanks!

Kun
  • Ylaine is currently working on #1
  • I am working on number 4 - building null distribution for 1KG set to determine distance between two adjacent SNPs.

IPS and Cancer

  • Need to be certain of SNPs used.
  • Can check other data sets (HL_003, HL_004, HL_008?)