topWindowStats {DEWSeq} | R Documentation

## stats for the top windows in each region

### Description

given window resutls and normalized counts, combine significant overlapping windows into regions and for each region, pick two candidate winodws:

1. with highest log2FoldChange and

2. with highest normalized mean in treatment samples (see parameter `treatmentCols`)

Return a data.frame with region information and stats, and for the selected windows, the following information:

- `unique_id` of the window

- start and end co-ordinates

- log2FoldChange

- normalized mean expression in treatment and control samples and

- individual normalized expression in replicates

### Usage

    topWindowStats(windowRes, padjCol = "padj", padjThresh = 0.05,
      log2FoldChangeCol = "log2FoldChange", log2FoldChangeThresh = 1,
      start0based = TRUE, normalizedCounts, treatmentCols,
      treatmentName = "treatment", controlName = "control", op = "max")

### Arguments

`windowRes` | `data.frame`, output from `resultsDEWSeq`
`padjCol` | `character`, name of the adjusted pvalue column (default: padj)
`padjThresh` | `numeric`, threshold for p-adjusted value (default: 0.05)
`log2FoldChangeCol` | `character`, name of the log2foldchange column (default: log2FoldChange)
`log2FoldChangeThresh` | `numeric`, threshold for log2foldchange value (default:1)
`start0based` | `logical`, TRUE (default) or FALSE. If TRUE, then the start positions in `windowRes` is considered to be 0-based
`normalizedCounts` | `data.frame` or `matrix`, normalized read counts per window. `rownames(normalizedCounts)` and `unique_id` column from `windoeRes` must match see `counts`, `vst` or `rlog`
`treatmentCols` | `character vector`, column names in `normalizedCounts` for treatment/case samples. The remaining columns in the data.frame will be considered control samples
`treatmentName` | `character`, treatment name, see Details (default: treatment)
`controlName` | `character`, control name, see Details (default: control)
`op` | `character`, can be one of `max` (default) or `min`. `max` returns windows with maximum log2FoldChange and mean normalized expression in the `treatmentCols` columns, `min` returns windows with minimum log2FoldChange and mean normalized expression

### Details

The output data.frame of this function has the following columns:

- `chromosome`: chromosome name

- `gene_id`: gene id

- `gene_name`: gene name

- `gene_region`: gene region

- `gene_type`: gene type annotation

- `regionStartId`: `unique_id` of the left most window, where a enriched region begins

- `region_begin`: start position of the enriched region

- `region_end`: end position of the enriched region

- `region_length`: length of the enrched region

- `strand`: strand info

- `Nr_of_region`: number of the current region

- `Total_nr_of_region`: total number of regions

- `log2FoldChange_min`: min. log 2 fold change in the region

- `log2FoldChange_mean`: average log 2 fold change in the region

- `log2FoldChange_max`: max. log 2 fold change in the region

- `unique_id.log2FCWindow`: unique_id of the window with largest log2FoldChange

- `begin.log2FCWindow`: start position of the window with largest log2FoldChange

- `end.log2FCWindow`: end of the window with largest log2FoldChange

- `log2FoldChange.log2FCWindow`: log2FoldChange of the window with largest log2FoldChange

- `treatmentName.mean.log2FCWindow`: mean of the normalized expression of the treatment samples for log2FCWindow, names in `treatmentCols` are used to calculate mean and treatmentName is from the parameter `treatmentName`

- `controlName.mean.log2FCWindow`: mean of the normalized expression of the control samples for log2FCWindow, `colnames(normalizedCounts)` not found in `treatmentCols` are used to calculate mean and controlName is from the parameter `controlName`

- the next columns will be normalized expression values of the log2FCWindow from individual treatment and control samples.

- `unique_id.meanWindow`: unique_id of the window with largest mean in all treatment samples from `treatmentCols`

- `begin.meanWindow`: start position of the mean window

- `end.meanWindow`: end position of the mean window

- `log2FoldChange.meanWindow`:log2FoldChange of the mean window

- `treatmentName.mean.meanWindow`: mean of the normalized expression of the treatment samples for meanWindow, names in `treatmentCols` are used to calculate mean and treatmentName is from the parameter `treatmentName`

- `controlName.mean.meanWindow`: mean of the normalized expression of the control samples for log2FCWindow, `colnames(normalizedCounts)` not found in `treatmentCols` are used to calculate mean and controlName is from the parameter `controlName`

- the next columns will be normalized expression values of the meanWindow from individual treatment and control samples

### Value

data.frame

### Examples

    data(slbpWindows)
    data(slbpVst)
    slbpList <- topWindowStats(slbpWindows,padjCol = 'pSlidingWindows.adj',
    normalizedCounts = slbpVst, treatmentCols = c('IP1','IP2'),
    treatmentName = 'SLBP',controlName = 'SMI')

[Package DEWSeq version 1.6.0 Index]