Kun:LabNotes/Haplotyping/2010-9-17
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Data Analysis[edit]
Read mapping[edit]
Mapping script Amplicon # reads % uniquely mapped % non-unique % unmappable 1A 7613296 66.42% 14.39% 19.20% 1F 7760883 65.75% 14.21% 20.04% 1G 5102454 52.91% 7.46% 39.62%
Looking for local enrichment of mapped reads.[edit]
- I used this script to group the per-site coverage into 10Mb windows, then visualize the average coverage using Idiographica.
File:GM20431 chr 1A.blockCoverage.png File:GM20431 chr 1F.blockCoverage.png File:GM20431 chr 1G.blockCoverage.png
SNP distribution[edit]
- I extracted variants from the pileup files using pileup2variants, then plot the distribution of known SNPs using this script and Idiographica.
File:GM20431 chr 1A SNP dist.png
Major conclusions[edit]
- Amplification from diluted chromosomes is an viable option.
- The chromosome concentration was over-estimated by roughly three folds.
- Compared with purified gDNA, the amplification curves on chromosomes tend to shoot up earlier. Therefore, we can't use the amplification curves on purified gDNA to estimate the number of chromosomes in each reaction.
- Three chromosomes (5,12,19) were present in the Amplicon 1A (amplified from small chromosomes, 10 chr/reaction). It is very likely that the other three amplicons (1B,1C,1D) from the same batch are good too.
- Amplicons 1F and 1G were amplified from small DNA fragments, and not usable.