Sas v9
SAS v9.4 is a software product developed by SAS Institute. It is a comprehensive data analysis and statistical software suite. The core function of SAS v9.4 is to provide users with tools for data management, analysis, and reporting.
Lab products found in correlation
5 311 protocols using sas v9
Evaluating Sow Vulva Scores and Litter Performance
ETDQ-7 and PEq5 Diagnostic Accuracy
Pig Growth Performance Evaluation
Variance Components and GWAS Analysis
Genomic Regions Associated with ROH
ROH islands were defined as clusters of runs that were > 1000 Kb with a minimum of 30 SNPs and found in more than 20 samples and analysed using Golden Helix SVS. For each sample, the proportion of SNPs in the ROH island was estimated. The mean proportion of SNPs per sample per ROH islands was determined using Proc MEANS procedure in SAS v9.4 [25 ]. The variance in mean proportion of SNPs in ROH islands amongst breeds was analysed using the Proc GLM in SAS v9.4 [25 ] using the following model:
Proportion of SNPs per ROH island = μ + Bi + e.where:
μ = overall mean;Bi =Breed effect and;e = random residual error
Comprehensive Multi-Omics Data Analysis
Hierarchical clustering in general used correlation as a measure of similarity and centroid-based linkage.
Simple differential analysis of groups using the RNA-Seq data was performed using two methods. In one method, the well-known t-statistic with a mildly stringent unadjusted p-value of 0.001 was combined with a fold change threshold of 1.5 to generate comparator lists. In a comparator method, we used the RNA-Seq differential method DESeq228 (link) with the same fold change threshold and a (multiple testing) corrected or adjusted p-value of 0.01. The linear model for the RNA-Seq analysis utilized 148 of the original 150 samples (specimens 4-4 and 51-4 omitted). The linear model was performed using SAS v9.4 PROC MIXED with subject as a random effect and terms for fixed effects of tissue type, collection site, and preservation protocol. Only effects with unadjusted p < 0.001 were kept for meta-analysis across genes.
We used Levene’s test (two-sided) for homogeneity of variance (SAS) when examining variation in miRNA expression by protocol.
Comparative Tubomanometry Curve Analysis
Multivariate Analysis of Low Back Pain
Extrusion Process Effects on Starch Properties
Spatial Empirical Bayes Smoothing for Rural MI Mortality
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