Top Tweets for #Adapt19
Recordings and slides of most talks at #Adapt19 #OfficialSMBE are now accessible on the meeting website https://t.co/K0Q5mIquLn
I came down with the flu yesterday and had to miss the last day of #adapt19. Sorry about laying down on the live tweet job. Thanks to @NedaBarghi and @vekutschera for taking over. Great meeting!
The science coming out of #adapt19 sure seems awesome, but am I wrong thinking that 11/15 speakers being white male maybe isn’t a very diverse snapshot of our community?
Great talk by Reinhard Buerger on the effects of epistasis and pleiotropy on local adaptation and the detection of adaptive loci. #Adapt19 #officialSMBE
Kaileigh Ahlquist on using machine learing using SWIF(r) to identify different modes of balancing selection #Adapt19 #OfficialSMBE
A fantastic talk by Himani Sachdeva. She discussed how a neutral haplotype block with many + and + alleles, can become shorter due to back crosding and recombination, and increase in frequency upon introgression. #OfficialSMBE #Adapt19
Luis-miguel Chevin presents empirical and theoretical results of adaptation to randomly changing environments #Adapt19 #OfficialSMBE
Tom Ellis talks about a quantitative framework to identify pleiotropy and GxE interactions #Adapt19 #OfficialSMBE
Reinhard Bürger on the effect of epistasis and pleiotropy on local adaptation and detection of QTLs #OfficialSMBE #Adapt19
The science coming out of #adapt19 sure seems awesome, but am I wrong thinking that 11/15 speakers being white male maybe isn’t a very diverse snapshot of our community?
@RuiBorg37123830 introduces a Bayesian method to estimate selection coefficient in E&R #OfficialSMBE #Adapt19
Kofler: looks like evolve and resequence using increasing selection can outperform GWAS for detecting alleles of small effect. But constant selection selection can be very bad for this. Also provides better estimates of distribution of effect sizes. #adapt19
Kofler: slowly increasing the strength of selection outperforms all forms/strengths of constant selection except when all allelic effects are equal. Note, this maximizes detection of QTN, but does not maximize response to selection of the phenotype. #adapt19
Robert Kofler: Optimizing the power to identify QTLs with evolve and resequence. Can changing the intensity of selection over the experiment help with mapping? Yes, starting weak and going strong reduces amount of hitchhiking #adapt19
Phillips: pattern of evolutionary response greatly simplifies (several orders of magnitude fewer SNPs), but still thousands of sights under selection. Interestingly, most of the selected sites are conditionally neutral in the ancestral population. #adapt19
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