This function returns a Q-Q plot with envelope using a more "continuous" approximation of quantiles.
qqplot_env_pois(sample_data, lambda, envelope_size = 100, ...)# S3 method for scppp
qqplot_env_pois(
sample_data,
lambda,
envelope_size = 100,
L = 10,
select_by = "entry",
entry_size = 200,
...
)
A ggplot object.
A numeric vector of sample data points or an S3 object for class 'scppp'.
A numeric value specifying the theoretical Poisson parameter.
A numeric value specifying the size of envelope on Q-Q plot (default 100).
not used.
A numeric value specifying the number of latent vectors included when estimate the Poisson parameter for each matrix entry. This is not useful if a numeric vector is used as input.
A character indicating whether entries should be selected:
Independent matrix entries with Poisson parameter estimates closest to lambda
One particular cell with UMI count mean closest to lambda
One particular gene with UMI count mean closest to lambda
This is not useful if a numeric vector is used as input.
A numeric value specifying the number of entries used to compare with the theoretical Poisson distribution. This is not useful if a numeric vector is used as input, or the entries are selected by cell or gene.
This is a function for Q-Q envelope plot used to compare whether given sample data points come from the theoretical Poisson distribution. By simulating repeated samples of the same size from the candidate theoretical distribution, and overlaying the envelope on the same figure, it provides a feeling of understanding the natural variation from the theoretical distribution.
If an S3 object for class 'scppp' is used as input and the stored result under "data" is a matrix, The GLM-PCA algorithm will be applied to estimate the Poisson parameter for each matrix entry. Then a specific number of entries will be selected as sample data points to compare with the theoretical Poisson distribution.
glmpcascpoisson