Definitely using swabs for all of the samples
PCR each DNA extract using species specific marker lp83. If the DNA doesn't amplify at this marker, it's not worth continuing with genotyping.
Also interested in adding melo??? a marker which can also be used for sex identification
Each run we are refining the SNP selection. David's work with the Illumina GoldenGate resulted in 94 SNPs of which 3-4 have already been eliminated.
This is relatively easy to achieve based on whether the SNPs amplify or not and whether the clusters are well defined in the raw reads from Fluidigm.
Tabulate the performance of all of the markers that have been used to date. Did they behave consistently in each run? (See David's SNPs).
Which SNPs behaved well but might have aged poorly (see SNPs where NTC had too much fluorescence).
End goal is to have ~300 high quality and a smaller chip of 48 (duplicated on each chip).
The other criteria we need to measure is the taza de error.
We need to re-run this calculation with the data set we have now (run for each consensus (th1, th1.5, th2).
All samples STA (pre-amplified) – not sure we want to do this, because not all samples need amplification if they are good quality. Exploring options to run the chip with some samples that are pre-amplified and some that are not.
Two machines: Juno (microfluidics and PCR) and BioMark (realtimePCR and measures fluorescence)
cycles of pre-amp
volume STA
cycles of genotyping
We each need to think about how this process can be organized to mitigate errors
Laura and Luis need to clean out all of the stocks and primers when they get into the lab because there are a lot of old reagents that are causing issues.
Compare error rates for three consensus
SNP naming needs to be constant in
Change names from David's genomic position to lp23… Maybe we need a more simple
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iberian_lynx
fluidigm
genotyping
SNP