corbetw2mat: Calculate correlations between columns of two matrices In lineup: Lining Up Two Sets of Measurements

 corbetw2mat R Documentation

Calculate correlations between columns of two matrices

Description

For matrices x and y, calculate the correlation between columns of x and columns of y.

Usage

```corbetw2mat(
x,
y,
what = c("paired", "bestright", "bestpairs", "all"),
corthresh = 0.9
)
```

Arguments

 `x` A numeric matrix. `y` A numeric matrix with the same number of rows as `x`. `what` Indicates which correlations to calculate and return. See value, below. `corthresh` Threshold on correlations if `what="bestpairs"`.

Details

Missing values (`NA`) are ignored, and we calculate the correlation using all complete pairs, as in `stats::cor()` with `use="pairwise.complete.obs"`.

Value

If `what="paired"`, the return value is a vector of correlations, between columns of `x` and the corresponding column of `y`. `x` and `y` must have the same number of columns.

If `what="bestright"`, we return a data frame of size `ncol(x)` by `3`, with the ith row being the maximum correlation between column i of `x` and a column of `y`, and then the `y`-column index and `y`-column name with that correlation. (In case of ties, we give the first one.)

If `what="bestpairs"`, we return a data frame with five columns, containing all pairs of columns (with one in `x` and one in `y`) with correlation `corthresh`. Each row corresponds to a column pair, and contains the correlation and then the `x`- and `y`-column indices followed by the `x`- and `y`-column names.

If `what="all"`, the output is a matrix of size `ncol(x)` by `ncol(y)`, with all correlations between columns of `x` and columns of `y`.

Author(s)

Karl W Broman, broman@wisc.edu

`distee()`, `findCommonID()`

Examples

```
data(expr1, expr2)

# correlations with paired columns
r <- corbetw2mat(expr1, expr2)
# top 10, by absolute value
r[order(abs(r), decreasing=TRUE)[1:10]]

# all pairs of columns with correlation >= 0.8
r_allpairs <- corbetw2mat(expr1, expr2, what="bestpairs", corthresh=0.6)

# for each column in left matrix, most-correlated column in right matrix
r_bestright <- corbetw2mat(expr1, expr2, what="bestright")

```

lineup documentation built on July 10, 2022, 5:05 p.m.