calc_norm_factors {seqsetvis} | R Documentation

## calc_norm_factors

### Description

Calculate normalization factors in a two step process:

### Usage

    calc_norm_factors(
      full_dt,
      value_ = "y",
      cap_value_ = "y_cap_value",
      by1 = "id",
      by2 = "sample",
      aggFUN1 = max,
      aggFUN2 = function(x) quantile(x, 0.95)
    )

### Arguments

`full_dt` | a data.table, as returned by ssvFetch*(..., return_data.table. = TRUE)
`value_` | character, attribute in full_dt to normalzie.
`cap_value_` | character, new attribute name specifying values to cap to.
`by1` | character vector, specifies attributes relevant to step 1.
`by2` | character vector, specifies attributes relevant to step 1 and 2.
`aggFUN1` | function called on value_ with by = c(by1, by2) in step 1.
`aggFUN2` | function called on result of aggFUN1 with by = by2 in step 2.

### Details

1) summarize every region for each sample (default summary function is max)

2) caclulate a value to cap each sample to based on regions (default is 95th quantile).

The uderlying assumption here is that meaningful enrichment is present at the majority of regions provided. If prevalence varies by a specific factor, say ChIP-seq targets with different characteristics - ie. when analyzing TSSes for H3K4me3 and an infrequent transcription factor it is more appropriate to specify appropriate quantile cutoffs per factor.

### Value

data.table mapping by2 to cap_value_.

### Examples

    calc_norm_factors(CTCF_in_10a_profiles_dt)
    calc_norm_factors(CTCF_in_10a_profiles_dt,
      aggFUN1 = mean, aggFUN2 = function(x)quantile(x, .5))

[Package seqsetvis version 1.8.0 Index]