CB2 (version 1.1)

run_estimation: A function to perform a statistical test at a sgRNA-level

Description

A function to perform a statistical test at a sgRNA-level

Usage

run_estimation(sgcount, design, group_a, group_b)

Arguments

sgcount

This data frame contains read counts of sgRNAs for the samples.

design

This table contains study design. It has to contain `group.`

group_a

The first group to be tested.

group_b

The second group to be tested.

Value

A table contains the sgRNA-level test result, and the table contains these columns:

  • `sgRNA`: The sgRNA identifier.

  • `gene`: The gene is the target of the sgRNA

  • `n_a`: The number of replicates of the first group.

  • `n_b`: The number of replicates of the second group.

  • `phat_a`: The proportion value of the sgRNA for the first group.

  • `phat_b`: The proportion value of the sgRNA for the second group.

  • `vhat_a`: The variance of the sgRNA for the first group.

  • `vhat_b`: The variance of the sgRNA for the second group.

  • `cpm_a`: The mean CPM of the sgRNA within the first group.

  • `cpm_b`: The mean CPM of the sgRNA within the second group.

  • `logFC`: The log fold change of sgRNA between two groups.

  • `t_value`: The value for the t-statistics.

  • `df`: The value of the degree of freedom, and will be used to calculate the p-value of the sgRNA.

  • `p_ts`: The p-value indicates a difference between the two groups.

  • `p_pa`: The p-value indicates enrichment of the first group.

  • `p_pb`: The p-value indicates enrichment of the second group.

  • `fdr_ts`: The adjusted P-value of `p_ts`.

  • `fdr_pa`: The adjusted P-value of `p_pa`.

  • `fdr_pb`: The adjusted P-value of `p_pb`.

Examples

Run this code
# NOT RUN {
library(CB2)
data(Evers_CRISPRn_RT112)
run_estimation(Evers_CRISPRn_RT112$count, Evers_CRISPRn_RT112$design, "before", "after")

# }

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