# colQuantiles: Calculates quantiles for each row (column) of a matrix-like... In DelayedMatrixStats: Functions that Apply to Rows and Columns of 'DelayedMatrix' Objects

## Description

Calculates quantiles for each row (column) of a matrix-like object.

## Usage

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25``` ```## S4 method for signature 'DelayedMatrix' colQuantiles( x, rows = NULL, cols = NULL, probs = seq(from = 0, to = 1, by = 0.25), na.rm = FALSE, type = 7L, force_block_processing = FALSE, ..., drop = TRUE ) ## S4 method for signature 'DelayedMatrix' rowQuantiles( x, rows = NULL, cols = NULL, probs = seq(from = 0, to = 1, by = 0.25), na.rm = FALSE, type = 7L, force_block_processing = FALSE, ..., drop = TRUE ) ```

## Arguments

 `x` A NxK DelayedMatrix. `rows` A `vector` indicating the subset of rows (and/or columns) to operate over. If `NULL`, no subsetting is done. `cols` A `vector` indicating the subset of rows (and/or columns) to operate over. If `NULL`, no subsetting is done. `probs` A numeric vector of J probabilities in [0, 1]. `na.rm` If `TRUE`, `NA`s are excluded first, otherwise not. `type` An integer specifying the type of estimator. See `stats::quantile()`. for more details. `force_block_processing` `FALSE` (the default) means that a seed-aware, optimised method is used (if available). This can be overridden to use the general block-processing strategy by setting this to `TRUE` (typically not advised). The block-processing strategy loads one or more (depending on `\link[DelayedArray]{getAutoBlockSize}()`) columns (`colFoo()`) or rows (`rowFoo()`) into memory as an ordinary base::array. `...` Additional arguments passed to specific methods. `drop` If `TRUE` a vector is returned if `J == 1`.

## Details

The S4 methods for `x` of type `matrix`, `array`, or `numeric` call `matrixStats::rowQuantiles` / `matrixStats::colQuantiles`.

## Value

a `numeric` `NxJ` (`KxJ`) `matrix`, where N (K) is the number of rows (columns) for which the J values are calculated.

## Author(s)

Peter Hickey

• `matrixStats::rowQuantiles()` and `matrixStats::colQuantiles()` which are used when the input is a `matrix` or `numeric` vector.

• stats::quantile

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10``` ```# A DelayedMatrix with a 'data.frame' seed dm_df <- DelayedArray(data.frame(C1 = rep(1L, 5), C2 = as.integer((0:4) ^ 2), C3 = seq(-5L, -1L, 1L))) # colnames, if present, are preserved as rownames on output colQuantiles(dm_df) # Input has no rownames so output has no rownames rowQuantiles(dm_df) ```

### Example output

```Loading required package: MatrixGenerics

Attaching package: ‘MatrixGenerics’

The following objects are masked from ‘package:matrixStats’:

colAlls, colAnyNAs, colAnys, colAvgsPerRowSet, colCollapse,
colCounts, colCummaxs, colCummins, colCumprods, colCumsums,
colMads, colMaxs, colMeans2, colMedians, colMins, colOrderStats,
colProds, colQuantiles, colRanges, colRanks, colSdDiffs, colSds,
colWeightedMeans, colWeightedMedians, colWeightedSds,
colWeightedVars, rowAlls, rowAnyNAs, rowAnys, rowAvgsPerColSet,
rowCollapse, rowCounts, rowCummaxs, rowCummins, rowCumprods,
rowCumsums, rowDiffs, rowIQRDiffs, rowIQRs, rowLogSumExps,
rowOrderStats, rowProds, rowQuantiles, rowRanges, rowRanks,
rowSdDiffs, rowSds, rowSums2, rowTabulates, rowVarDiffs, rowVars,
rowWeightedSds, rowWeightedVars

Attaching package: ‘BiocGenerics’

The following objects are masked from ‘package:parallel’:

clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
clusterExport, clusterMap, parApply, parCapply, parLapply,
parLapplyLB, parRapply, parSapply, parSapplyLB

The following objects are masked from ‘package:stats’:

The following objects are masked from ‘package:base’:

anyDuplicated, append, as.data.frame, basename, cbind, colnames,
dirname, do.call, duplicated, eval, evalq, Filter, Find, get, grep,
grepl, intersect, is.unsorted, lapply, Map, mapply, match, mget,
order, paste, pmax, pmax.int, pmin, pmin.int, Position, rank,
rbind, Reduce, rownames, sapply, setdiff, sort, table, tapply,
union, unique, unsplit, which.max, which.min

Attaching package: ‘S4Vectors’

The following object is masked from ‘package:Matrix’:

expand

The following object is masked from ‘package:base’:

expand.grid

Attaching package: ‘DelayedArray’

The following objects are masked from ‘package:base’:

aperm, apply, rowsum

Attaching package: ‘DelayedMatrixStats’

The following objects are masked from ‘package:matrixStats’:

colAnyMissings, rowAnyMissings

0% 25% 50% 75% 100%
C1  1   1   1   1    1
C2  0   1   4   9   16
C3 -5  -4  -3  -2   -1
0%  25% 50% 75% 100%
1 -5 -2.5   0 0.5    1
2 -4 -1.5   1 1.0    1
3 -3 -1.0   1 2.5    4
4 -2 -0.5   1 5.0    9
5 -1  0.0   1 8.5   16
```

DelayedMatrixStats documentation built on Feb. 5, 2021, 2:04 a.m.