pois_ci_profile: Calculate position-wise confidence intervals

In ilia-kats/RiboSeqTools: Tools for analysis of selective ribosome profiling (SeRP) data

Description

For a given gene, confidence intervals of read counts are calculated for each position.

Usage

pois_ci_profile(
  data,
  gene,
  samples,
  exp,
  rep,
  bin,
  window_size,
  conf.level = 0.95,
  ignore_genecol = FALSE
)

Arguments

data	A serp_data object.
gene	Name of the gene/ORF.
samples	Sample name. If missing, all samples will be used.
exp	Experiment name(s). If missing, all experiments will be used.
rep	Replicate name(s). If missing, all replicates will be used.
bin	Binning to use. If missing, will be automatically determined.
window_size	Neighborhood size in nucleotides. Will be automatically converted to codons if binning by codons.
conf.level	Confidence level.
ignore_genecol	If TRUE, assumes that the given gene is the gene identifier contained in the gene column of the reference table. If FALSE, assumes that the given gene corresponds to the genename_column setting in the defaults.

Details

At each position within the gene, read counts within a window_size-wide neighborhood are summed up and used for CI calculation. A confidence interval is calculated using pois_ci.

Value

A tibble with the following columns:

exp

Experiment name.

rep

Replicate name.

sample

Sample name.

winmid

Center of the neighborhood for which the CI was calculated.

counts

Raw counts at position winmid.

RPM

RPM at position winmid.

win_counts

Total read counts within the neighborhood centered at winmid.

win_RPM

Total RPM within the neighborhood centered at winmid.

counts_mean

Estimated counts.

RPM_mean

Estimated RPM.

lo_CI_counts

Lower confidence bound for raw counts.

hi_CI_counts

Upper confidence bound for raw counts.

lo_CI

Lower confidence bound for RPM.

hi_CI

Upper confidence bound for RPM.

ilia-kats/RiboSeqTools documentation built on Oct. 5, 2020, 7:41 p.m.