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The first 10 time points of all datasets were discarded to avoid unstable magnetization and to ensure the participants adapted the scanning circumstance.
These datasets were discarded from our study.
Probesets not common across the datasets were discarded.
Incomplete datasets were discarded, leading to 153 complete sets.
Nogaps datasets were discarded due to their major effect on rates and age estimations (see below).
EF-1α and LWRh datasets were discarded from SAMOVA due to their poor genetic structuring (global ΦST statistic = 0.35, p-value < 0.01 for EF-1 α and p-value > 0.01 for LWRh).
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The majority of uncalled loci in typical 2b-RAD datasets are discarded because of low coverage (Meyer, unpublished observations) so this problem could be mitigated with deeper sequencing.
If a proportion of the A. americanum ESTs that failed to match the I. scapularis datasets is discarded to control for reference quality, higher values for homology between A. americanum and I. scapularis are estimated: 34% matching between A. americanum ESTs and the I. scapularis predicted peptides, 35% matching with I. scapularis contigs, and 43% matching with I. scapularis singletons.
The first 500,000 1,000,000 generations (again, depending on the dataset) were discarded as burn-in.
The first five volumes of each participant's dataset were discarded to allow for T1 equilibration.
Initially, the first image from each functional dataset was discarded to minimize T1 equilibration artifacts.
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