Use the numerical generative process to calibrate the model about sccomp HOT 11 OPEN

Calibrate inference of associations

• Generate 100 datasets with the same total counts per subject (M size vector, where M is the number of subjects), for each dataset
• Number of subjects 30, number of categories 20
• Design matrix would have an intercept column and a factor of interest between -1 and 1
• Setup coefficient to have same intercept (for simplicity), and zero slope
• Generate the data
• Execute sccomp (visit homepage of this repository)
• • FOR INSTALLATION DO: devtools::install_github("stemangiola/sccomp")
• • library(sccomp)
• • Follow the readme
• Count how many categories were labelled as significantly changing (by default we are using the 95% credible interval. Which means that we expect 5% of calls to be false)

from sccomp.

"Setup coefficient to have same intercept (for simplicity), and zero slope"
Are there any other constraints on coefficient? i.e. integer ? Range ?
Also, I assume that "zero slope" means coeff=(beta0,beta0,...,beta0; beta1,beta1,...,beta1); that the first column repeats 20 times.

from sccomp.

"Setup coefficient to have same intercept (for simplicity), and zero slope"
Are there any other constraints on coefficient? i.e. integer ? Range ?

Execute the code at the homepage of this repository and you will see what coefficients you get for a real dataset. You can get the range from those (except the intercept that should be zero for this test)

from sccomp.

About integer or not, it is exactly the same. When you do matrix multiplication between design and coefficient is the same.

from sccomp.

Hi Stefano,

I have successfully created 100 data frames from my function. To detect the change, do I need to use sccomp library? Or I shall find out a way to do that ?

from sccomp.

Hi Stefano,

I have successfully created 100 data frames from my function. To detect the change, do I need to use sccomp library? Or I shall find out a way to do that ?

Yes, run sccomp on your data set. See example dataset from github README. Start from a few and try to draw descriptive statistics.

from sccomp.

which function in the sccomp is used for detecting variation ?

from sccomp.

As I noticed the fuction: res =
counts_obj %>%
sccomp_glm(
~ type,
sample, cell_group, count,
approximate_posterior_inference = FALSE
)
When analyzing multiple data frames, do I need to merge the data frames, or specifying different data frame by "cell goup " above? Also, type=category, count=count, sample=subject in our dictionary, right?

from sccomp.

if you analyse different studies no, you analyse them independently. I don't know what you mean by data frames. Data frame can be anything. Please be more precise.

Also, type=category, count=count, sample=subject in our dictionary, right?

yes

from sccomp.

if you analyse different studies no, you analyse them independently. I don't know what you mean by data frames. Data frame can be anything. Please be more precise.

Also, type=category, count=count, sample=subject in our dictionary, right?

yes

By data frames, I mean the output simulated data frames from my numeric generation process.

from sccomp.

one data frame includes M categories and N subjects.

another data frame includes M categories and N subjects.

one subject does constitute a very small dataset that cannot be used for regression, size = 1

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