A dataset containing gene expression of PTPRG in 60k microglia cells from the PsychAD Consortium from 299 subjects. Of these, 149 subjects have Alzheimer's disease, and 150 are neurotypical controls.
Format
A data frame with 60481 rows (i.e. cells) and 6 variables:
- SubID
subject identifer
- Sex
Sex
- Dx
Diagnosis: AD or Control
- Age
subject age
- PTPRG
number of RNA-seq counts for this gene
- libSize
total number of RNA-seq reads for this cell
Examples
data(PsychAD)
# model formula
form <- PTPRG ~ Dx + Age + Sex + offset(log(libSize)) + (1|SubID)
# fit negative binomial mixed model
fam <- negative.binomial(NA)
fit <- fastglmm(form, PsychAD, family=fam)
summary(fit)
#> Generalized linear mixed model fit by PQL ['fastglmm']
#> Family: Negative Binomial(0.2443) ( log )
#> Formula: PTPRG ~ Dx + Age + Sex + offset(log(libSize)) + (1 | SubID)
#>
#> Coefficients:
#> Estimate Std. Error df t value Pr(>|t|)
#> (Intercept) -8.577681 0.311172 149.9 -27.566 <2e-16 ***
#> DxAD 1.102755 0.073541 145.6 14.995 <2e-16 ***
#> Age -0.007262 0.003775 148.2 -1.923 0.0563 .
#> SexMale -0.103277 0.075756 145.7 -1.363 0.1749
#> ---
#> Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
#>
#> Residual df: 60227.2
#>
#> Variance components:
#> sigSq_g: 0.4803
#> sigSq_e: 8.17
#> delta: 17.01
# Variance partitioning analysis
varpart(fit)
#> Dx Age Sex SubID CountNoise Residuals
#> 0.0133097371 0.0002197195 0.0001160483 0.0210313340 0.3062036641 0.6591194970