Author: Nathalie Pamir; Calvin Pan; Deanna L. Plubell; Patrick M. Hutchins; Chongren Tang; Jake Wimberger; Angela Irwin; Thomas Q. de Aguiar Vallim; Jay W. Heinecke; Aldons J. Lusis
Title: Genetic control of the HDL proteome Document date: 2018_8_31
ID: hx7n4xfo_32
Snippet: . CC-BY-NC-ND 4.0 International license is made available under a The copyright holder for this preprint (which was not peer-reviewed) is the author/funder. It . https://doi.org/10.1101/405811 doi: bioRxiv preprint Heritability. Broad sense heretibiliaty scores were calculated for each protein using R package (sommer) using the formula H2= genetic variance / (genetic variance + residual variance) Statistical analyses. Data are means ± SEMs. Line.....
Document: . CC-BY-NC-ND 4.0 International license is made available under a The copyright holder for this preprint (which was not peer-reviewed) is the author/funder. It . https://doi.org/10.1101/405811 doi: bioRxiv preprint Heritability. Broad sense heretibiliaty scores were calculated for each protein using R package (sommer) using the formula H2= genetic variance / (genetic variance + residual variance) Statistical analyses. Data are means ± SEMs. Linear correlation among the HDL metrics of the 93 strains were assessed with pearson correlations and the association of the proteins were assessed by spearman correlations both were followed with Bonferroni-Holm post-hoc correction for multiple comparisons. Data were analyzed with Prism and R software. Data and software availability. The MS/MS datasets produced in this study are available in the PRIDE consortium (ProteomXchange submission ref: 1-20180406-10713) and in the UCLA based public database established to harbor HMDP related data (https://systems.genetics.ucla.edu/data).
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