Empirical comparisons of different statistical models to identify and validate kernel row number-associated variants from structured multi-parent mapping populations …
J Yang, CTE Yeh, RK Ramamurthy, X Qi… - G3: Genes …, 2018 - academic.oup.com
Advances in next generation sequencing technologies and statistical approaches enable
genome-wide dissection of phenotypic traits via genome-wide association studies (GWAS).
Although multiple statistical approaches for conducting GWAS are available, the power and
cross-validation rates of many approaches have been mostly tested using simulated data.
Empirical comparisons of single variant (SV) and multi-variant (MV) GWAS approaches have
not been conducted to test if a single approach or a combination of SV and MV is effective …
genome-wide dissection of phenotypic traits via genome-wide association studies (GWAS).
Although multiple statistical approaches for conducting GWAS are available, the power and
cross-validation rates of many approaches have been mostly tested using simulated data.
Empirical comparisons of single variant (SV) and multi-variant (MV) GWAS approaches have
not been conducted to test if a single approach or a combination of SV and MV is effective …
Empirical comparisons of different statistical models to identify and validate kernel row number-associated variants from structured multi-parent mapping populations …
YJL Yang JinLiang, YCT Yeh ChengTing… - 2018 - cabidigitallibrary.org
Advances in next generation sequencing technologies and statistical approaches enable
genome-wide dissection of phenotypic traits via genome-wide association studies (GWAS).
Although multiple statistical approaches for conducting GWAS are available, the power and
cross-validation rates of many approaches have been mostly tested using simulated data.
Empirical comparisons of single variant (SV) and multi-variant (MV) GWAS approaches have
not been conducted to test if a single approach or a combination of SV and MV is effective …
genome-wide dissection of phenotypic traits via genome-wide association studies (GWAS).
Although multiple statistical approaches for conducting GWAS are available, the power and
cross-validation rates of many approaches have been mostly tested using simulated data.
Empirical comparisons of single variant (SV) and multi-variant (MV) GWAS approaches have
not been conducted to test if a single approach or a combination of SV and MV is effective …
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