This function processes summary statistics table generated by differential expression analysis
like limma
or DESeq2
and produces a message about pvalues and fold change used.
produce.cutoff.message(
data,
FCmin,
FCmax,
FCstep,
FDRflag,
p.min,
p.max,
p.step
)
Summary statistics table from limma or DEseq2, where each row is a gene.
The minimum starting fold change cutoff to be checked, so the minimum fold change cutoff to be evaluated will be FCmin + FCstep, FCmin default = 1.
The maximum fold change cutoff to be checked, default = 2.
The step from the minimum to maximum fold change cutoff, one step increase at a time, default = 0.01.
The column name of the False Discovery Rate (FDR) in the summary statistics table.
The minimum starting FDR cutoff to be checked, so the minimum fold change cutoff to be evaluated will be p.min + p.step, p.min default = 0.
The maximum FDR cutoff to be checked, default = 0.2.
The step from the minimum to maximum fold change cutoff, one step increase at a time, default = 0.005.