Athurva Gore/LabNotes/2009-8-18: Difference between revisions
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** LeeXGenes (on opposite strand to target cDNA) | ** LeeXGenes (on opposite strand to target cDNA) | ||
** ZhangSNP (on opposite strand to target cDNA) | ** ZhangSNP (on opposite strand to target cDNA) | ||
** FlyDup901 | |||
* '''CURRENTLY RUNNING:''' | * '''CURRENTLY RUNNING:''' | ||
** FlyDup5279 | ** FlyDup5279 | ||
* '''TO RERUN:''' | * '''TO RERUN:''' | ||
Line 30: | Line 30: | ||
** Running script to separate our SNP calls and 1KG SNP calls by in-range and out-of-range | ** Running script to separate our SNP calls and 1KG SNP calls by in-range and out-of-range | ||
** NOTE: File Dr. Zhang provided uses a slightly inaccurate start position; needs to be incremented by 1 for the residue based coordinate system. End is accurate. | ** NOTE: File Dr. Zhang provided uses a slightly inaccurate start position; needs to be incremented by 1 for the residue based coordinate system. End is accurate. | ||
==Specific vs. Nonspecific capture== | |||
* For our SNP calls: | * For our SNP calls: | ||
** FOUND THAT 3190/20762 were NONSPECIFIC | ** FOUND THAT 3190/20762 were NONSPECIFIC | ||
** ~85% specific capture | ** ~85% specific capture | ||
* Want to separate false positives from true positives in our SNPs. | * Want to separate false positives from true positives in our SNPs. | ||
* NEXT | ==Comparison of our SNP calls to 1KG== | ||
* Compared our SNP calls to 1KG | |||
** Found (out of 20,761 SNPs): | |||
** 16319 hits (~78.5%) | |||
** 598 miscalls (~3%) | |||
** 3844 misses (~18.5%) | |||
* Need to determine reasons for this | |||
** Plot of quality and coverage: | |||
==NEXT STEPS:== | |||
* Look at IPS data; plot quality and coverage of SNPs. | |||
* Run bowtie on runs from NA12878 that have high false positives - Done | |||
* See if there is a pattern; can we separate these false positives out somehow? | |||
=NA12878 High False Positive Reads= | =NA12878 High False Positive Reads= | ||
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*** Merge s_4 through s_7 in HL002, merge s_4 and s_5 in HL003 | *** Merge s_4 through s_7 in HL002, merge s_4 and s_5 in HL003 | ||
*** Run Bowtie-SAM script on these merged sets; check results | *** Run Bowtie-SAM script on these merged sets; check results | ||
*** | *** Bowtie-SAM has been run on both HL003 and HL002. | ||
* HL002 has a TON of SNPs. | |||
** 185k! | |||
** Something is very odd here. | |||
* Noticed that HL002 and one set from HL003 both used size-selection. | |||
** Not sure about Billy's results | |||
* Looked for a homozygous overrepresentation. | |||
** In HL002, definite presence of homozygous SNPs over heterozygous SNPs. | |||
* Next Steps: | |||
** Check both of these samples against dbSNP | |||
** Check both of these samples against 1KG | |||
** Is there anything similar among the false positives? |
Latest revision as of 02:44, 19 August 2009
[edit]
Probe Generation[edit]
- 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)
- FlyDup901
- CURRENTLY RUNNING:
- FlyDup5279
- TO RERUN:
- TDMR Set (Also check if out-of-memory happens again...maybe run on Miner?)
- Look into this tomorrow
- TDMR Set (Also check if out-of-memory happens again...maybe run on Miner?)
- Check numbering of new probes
- Appears to be slightly inaccurate as well.
- For residue coordinate system:
- End position should be increased by 1
- Start position should be increased by 2
- For space coordinate system:
- End position should be increased by 1
- Start position should be increased by 1
Exome SNPs - NA12878[edit]
- Currently:
- Running script to separate our SNP calls and 1KG SNP calls by in-range and out-of-range
- NOTE: File Dr. Zhang provided uses a slightly inaccurate start position; needs to be incremented by 1 for the residue based coordinate system. End is accurate.
Specific vs. Nonspecific capture[edit]
- For our SNP calls:
- FOUND THAT 3190/20762 were NONSPECIFIC
- ~85% specific capture
- Want to separate false positives from true positives in our SNPs.
Comparison of our SNP calls to 1KG[edit]
- Compared our SNP calls to 1KG
- Found (out of 20,761 SNPs):
- 16319 hits (~78.5%)
- 598 miscalls (~3%)
- 3844 misses (~18.5%)
- Need to determine reasons for this
- Plot of quality and coverage:
NEXT STEPS:[edit]
- Look at IPS data; plot quality and coverage of SNPs.
- Run bowtie on runs from NA12878 that have high false positives - Done
- See if there is a pattern; can we separate these false positives out somehow?
NA12878 High False Positive Reads[edit]
- Locations
- 07282009_HL002, Lanes 4-7
- 08052009_HL003, Lanes 4-5
- Storing data on genome-miner:/media/TmpStore1/AG_Scratch/Exome/NA12878
- Using this sample for validation
- First step, need to map these reads.
- Start out with reads on a per experiment basis
- Merge s_4 through s_7 in HL002, merge s_4 and s_5 in HL003
- Run Bowtie-SAM script on these merged sets; check results
- Bowtie-SAM has been run on both HL003 and HL002.
- HL002 has a TON of SNPs.
- 185k!
- Something is very odd here.
- Noticed that HL002 and one set from HL003 both used size-selection.
- Not sure about Billy's results
- Looked for a homozygous overrepresentation.
- In HL002, definite presence of homozygous SNPs over heterozygous SNPs.
- Next Steps:
- Check both of these samples against dbSNP
- Check both of these samples against 1KG
- Is there anything similar among the false positives?