Description Usage Arguments Details Value Examples
Fit negative binomial model to obtain p-values for interactions.
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interaction.data |
data.table object containing interaction counts. Must contain columns distance, count, and bait_trans_count. |
distance.bins |
Number of bins to split distance into. Models are fit separately in each bin. |
distribution |
Name of distribution of the counts. Options are 'negative-binomial', 'poisson', 'truncated-poisson', and 'truncated-negative-binomial' |
bait.filters |
Vector of length two, where the first element corresponds to the lower-end filter and the second to the upper-end filter. When global multiple testing correction is performed, altering the bait filtering settings may affect the number of significant results. |
target.filters |
Vector of length two, giving lower and higher filter, respectively. Changing this filtering setting may affect multiple testing correction by altering the number of tests performed. |
adjustment.terms |
Character vector of extra terms to adjust for in the model fit. |
maxit |
Maximum number of IWLS iterations for fitting the model (passed to |
epsilon |
Positive convergence tolerance for Poisson and negative binomial models. Passed to |
cores |
Integer value specifying how many cores to use to fit model for cis-interactions. |
trace |
Logical indicating if output should be produced for each of model fitting procedure. Passed to |
verbose |
Logical indicating whether to print progress reports. |
interim.data.dir |
Path to directory to store intermediate QC data and plots. |
Fit a negative binomial model for obtaining p-value for interactions. The data is first sorted by distance, and models are fit separately in each quantile of the distance-sorted data.
Interactions data with expected number of interactions and p-values added.
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