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By relating phenotypic and genetic variation, linkage and association mapping allow us to identify the genetic basis of complex traits (Mackay et al. 2009).
These randomly permuted mapping allow us to empirically derive the null distributions for the number of TE-containing transcripts that will be found at any normalized rank.
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Sequence information for RFLP and SSR markers used in QTL mapping allowed us to determine their physical positions through the use of BLASTN and e-PCR searches.
Geographic mapping allowed us the identification of the zones in South Florida where injuries were occurring.
Our preliminary stratigraphic study coupled with mapping allows us to construct a composite balanced cross-section through the Kuru Chu valley in eastern Bhutan which provides the first image of the geometry and amount of shortening through Bhutan.
Understanding the combined influence of pulse density and grid cell sizes on AGC prediction and mapping allows us to understand how well AGC estimates can be compared over time, as LiDAR technology and flight characteristics vary.
Linkage analysis after whole genome scanning and fine mapping allowed us to localize the rex coat trait in a 0.5 cM region on OCU14.
The second mapping allowed us to verify the circularization of plastid genome.
Sammon mapping allows us to see that the magnitude of dissimilarities between day types varies across the map.
However, the high throughput advantage of Optical Mapping allows us to distinguish such random errors from legitimate genomic events.
Such a mapping allows us to infer the evolutionary events that gave rise to that particular gene tree.
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