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Adding more markers led to a significant reduction in bias.
More markers led to less variance but did not markedly affect the result.
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This analysis shows whether scoring more markers leads to increasing number of identified genotypes.
This set of markers led to a more reliable structure (in base to knowledge on genetic and geographical origin and use of the cultivars) and more conservative association results (lower P-values and R) than a set of 261 SNP markers (data not shown).
A more recent work employing EST-SSR, genomic SSR and EST-STS markers led to the construction of genetic maps of two lowland switchgrass genotypes.
On the other hand, as noted by Badea et al.[ 50], the lower PIC values of DArT markers lead to a more defined genetic structure of accessions from distant geographic regions or genetic origin and thus can be of advantage in cluster analyses.
We found in our previous work that incorporation of more markers not only leads to more accurate parameter estimates, but also allows a better characterization of the progression dynamics of smaller and smaller subintervals of the cell cycle (Orlando et al., 2009).
Using more divergent parents led to maps with more markers, but the trends were the same.
With kNNI, a smaller number of nonmissing data points at a given marker leads to a more accurate estimate of its distance from all other markers.
However, if more markers are included in the assay, this may lead to an increase of the cost and effort of the method.
For example, a cross between EM1624 (six markers) and 'Albion' (seven markers) would lead to a progeny segregating for 11 out of a total of 13 possible resistance markers (there are more markers than QTL due to shared QTL having different allele sizes associated with each QTL in the most closely linked marker).
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