Description Usage Arguments Value Author(s) See Also
Creates simulated null distribution of average t statistics for regions classified as over- or underexpressed, and obtains p-values for observed over- and underexpressed regions based on this simulated null.
1 2 3  | 
regions | 
 data frame of regions to obtain p-values
for: specifically the   | 
dbfile | 
 Database file used to obtain the
  | 
tablename | 
 Name of the table in   | 
num.perms | 
 Number of permutations to use to create the null distribution.  | 
group | 
 0/1 vector denoting group labels for the samples used in analysis  | 
est.params | 
 return from   | 
chromosome | 
 Chromosome you are analyzing. Currently only runs one chromosome at a time.  | 
colsubset | 
 Colsubset argument used to create
  | 
adjustvars | 
 Optional matrix of adjustment variables (e.g. measured confounders, output from SVA, etc.) to use in fitting linear models to each nucleotide.  | 
nonzero | 
 If TRUE, use the median of only the nonzero counts as the library size adjustment.  | 
scalefac | 
 A log transformation is used on the count tables, so zero counts present a problem. What number should we add to the entire matrix before running the models? Defaults to 32.  | 
chunksize | 
 How many rows of the database should be processed at a time?  | 
colmeds | 
 If NULL, the column medians are calculated
using   | 
A vector having length equal to the number of rows in
regions, giving a p-value for each region of state 3
or 4 in regions.
Alyssa Frazee
getLimmaInput,getTstats,getRegions
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