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Finally, given the high marker density available nowadays, the simpler method should be preferred as it gives accurate results in a reasonable computing time.
We investigated the extent to which population sample size within the WGS datasets impacts the marker density available for map generation, as well as the length of the final LD maps.
The catfish integrated map presented here substantially increases linkage marker density available for QTL studies and connects the majority of the catfish genetic markers to physical sequence BAC contigs through the use of BES microsatellites.
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This process could be amplified to a larger set of in silico detected SNVs in expressed genes in order to increase the marker density in available and future genetic maps.
Taking into account a former QTL detection experiment [ 16] and other results [ 4, 9, 10, 15] that all showed the presence of a major QTL for seedlessness on LG 18, we replaced dominant markers and increased marker density with available and newly developed co-dominant markers.
A comprehensive scan under the available marker density was performed with all chromosomes being covered.
Consequently, QTL detection power in our study was limited by the available marker density and might have been enhanced by increasing the genotyping depths of the 135 parental lines.
In the present study, this assumption seems to be reasonable as for the five plant species examined the available marker density was considerably lower than that required for genome-wide association mapping.
Available linkage maps have low marker density due to limitation in available markers; therefore new technologies that detect genome-wide polymorphisms are still needed to discover a large number of new markers for construction of high-resolution maps.
We first sought to assess the added power conferred by addition of EMI markers to an existing AM single nucleotide polymorphism (SNP) panel [ 22], using markers on two chromosomes of different length and with differing marker density in previously published and available AIMs panels - namely, chromosomes 4 and 22.
The correlation between TBV and EBV increased as the marker density increased, because more information was available for predicting QTL genotypes, but most notably for 'BayesB'.
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