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{{ AGLabEntry|2009-8-27|2009-8-29 }} =To Do= * Forms for Tech Transfer Office * Invoice for Zymo =Removing Reads with Multiple SNPS= ==DF699== * Took results from removal of reads w/SNPs in the last 15 bp * Removed reads that had more than one SNP. * 9386 hits, 1103 misses * Don't do any better than just removing those with SNPs in the last 15 bp. ** Probably not the approach to take. =Remaining options= * Considered: ** Removing reads w/multiple SNPs ** Removing reads w/SNPs near the end (removes many bad SNPs, but also some good SNPs) ** Trimming reads w/SNPs near the end (removes many bad SNPs as well; retains more good and bad though) * Still remaining: ** Reducing quality score of SNPs - probably won't see any better results than above ** New Idea: Split reads into two sections; first 25, last 15? * For now, we will go with removing reads with SNPs near the end =IPS and Cancer= * For Proposal, preliminary data is needed of the difference between DF699 and fibroblast. ** Want this data to be high quality * Started with results that removed reads w/ SNPs withing 15 bp of the end * Then ran pileup2variantsPair with min coverage of 8 and min quality of 20. * Used a chi-squared test and removed SNPs that scored lower than 6. * Found: ** 193 SNPs ** 145 not at dbSNP locations (the above 48 are probably just miscalls in one case due to biased capture) *** 128 Loss-of-Heterozygosity *** 13 Gain-of-Heterozygosity *** 4 Doubles ** If these GOH mutations are investigated, only 5 are nonsynonymous *** 3 of these appear in the COSMIC set ** Decided to check both LOH and GOH mutations to see if any are valid. *** SIFT: Does it report ref/call? Or does it report in same order? *** None are classified as purely damaging by SIFT; one is damaging but with low confidence * Need to investigate data itself, check over SNPs. * Decided to compare to a filter where SNPs had a minimum coverage of 4 instead ** Will pass just GOH to SIFT, check to see if analysis for presentation was correct
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