Fold change and p-value estimations for simulations
Usage
deseq_fun_est(
metadata_list,
countdata_list,
alpha_level = 0.1,
group_colname,
sample_colname,
num_cores = 1,
ref_name = NULL
)Arguments
- metadata_list
: list of metadata
- countdata_list
: list of otu count data
- alpha_level
The significance level for determining differential expression. Default is 0.1.
- group_colname
column names of the groups or conditions
- sample_colname
column names of the samples
- num_cores
: number of cores
- ref_name
reference level for fold change calculation. If NULL, the reference level is determined automatically — by default, the factor level that comes first is used as the reference.
Value
A list logfoldchange log fold change estimates
logmean is the log mean count for taxa (arithmetic mean for taxa across all subjects)
dispersion: dispersion estimates for each taxa
deseq_estimate is a dataframe containing results from deseq baseMean,log2FoldChange, lfcSE, pvalue, padj
normalised_count is the normalised count data