Description Usage Arguments Value References Examples
This method estimates Irreproducible Discovery Rates (IDR) for peaks in replicated ChIPseq experiments.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18  estimate_idr1d(
rep1_df,
rep2_df,
value_transformation = c("identity", "additive_inverse", "multiplicative_inverse",
"log", "log_additive_inverse"),
ambiguity_resolution_method = c("overlap", "midpoint", "value"),
remove_nonstandard_chromosomes = TRUE,
max_factor = 1.5,
jitter_factor = 1e04,
max_gap = 1L,
mu = 0.1,
sigma = 1,
rho = 0.2,
p = 0.5,
eps = 0.001,
max_iteration = 30,
local_idr = TRUE
)

rep1_df 
data frame of observations (i.e., genomic peaks) of replicate 1, with at least the following columns (position of columns matter, column names are irrelevant):
 
rep2_df 
data frame of observations (i.e., genomic peaks) of replicate 2, with the following columns (position of columns matter, column names are irrelevant):
 
value_transformation 
the values in
either  
ambiguity_resolution_method 
defines how ambiguous assignments (when one interaction in replicate 1 overlaps with multiple interactions in replicate 2 or vice versa) are resolved. Available methods:
 
remove_nonstandard_chromosomes 
removes peaks containing
genomic locations on nonstandard chromosomes using
 
max_factor 
numeric; controls the replacement values for  
jitter_factor 
numeric; controls the magnitude of the noise that
is added to  
max_gap 
integer; maximum gap in nucleotides allowed between two anchors for them to be considered as overlapping (defaults to 1, i.e., overlapping anchors)  
mu 
a starting value for the mean of the reproducible component.  
sigma 
a starting value for the standard deviation of the reproducible component.  
rho 
a starting value for the correlation coefficient of the reproducible component.  
p 
a starting value for the proportion of reproducible component.  
eps 
Stopping criterion. Iterations stop when the increment of loglikelihood is < eps*loglikelihood, Default=0.001.  
max_iteration 
integer; maximum number of iterations for IDR estimation (defaults to 30)  
local_idr 
see 
List with three components, (rep1_df
, rep2_df
,
and analysis_type
) containing the interactions from input
data frames rep1_df
and rep2_df
with
the following additional columns:
column 1:  chr  character; genomic location of peak 
chromosome (e.g., "chr3" ) 
column 2:  start  integer; genomic location of peak  start coordinate 
column 3:  end  integer; genomic location of peak  end coordinate 
column 4:  value  numeric; pvalue, FDR, or heuristic used to rank the peaks 
column 5:  rep_value  numeric; value of corresponding
replicate peak. If no corresponding peak was found, rep_value is set
to NA . 
column 6:  rank  integer; rank of the peak, established by value column, ascending order 
column 7:  rep_rank  integer; rank of corresponding
replicate peak. If no corresponding peak was found, rep_rank is
set to NA . 
column 8:  idx  integer; peak index, primary key 
column 9:  rep_idx  integer; specifies the index of the
corresponding peak in the other replicate (foreign key). If no
corresponding peak was found, rep_idx is set to NA . 
column 10:  idr  IDR of the peak and the
corresponding peak in the other replicate. If no corresponding
peak was found, idr is set to NA .

Q. Li, J. B. Brown, H. Huang and P. J. Bickel. (2011) Measuring reproducibility of highthroughput experiments. Annals of Applied Statistics, Vol. 5, No. 3, 17521779.
1 2 3 4  idr_results < estimate_idr1d(idr2d:::chipseq$rep1_df,
idr2d:::chipseq$rep2_df,
value_transformation = "log")
summary(idr_results)

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