Perform MR of multiple exposures and multiple outcomes. This plots the results.

## Usage

```
forest_plot(
mr_res,
exponentiate = FALSE,
single_snp_method = "Wald ratio",
multi_snp_method = "Inverse variance weighted",
group_single_categories = TRUE,
by_category = TRUE,
in_columns = FALSE,
threshold = NULL,
xlab = "",
xlim = NULL,
trans = "identity",
ao_slc = TRUE,
priority = "Cardiometabolic"
)
```

## Arguments

- mr_res
Results from

`mr()`

.- exponentiate
Convert effects to OR? Default is

`FALSE`

.- single_snp_method
Which of the single SNP methosd to use when only 1 SNP was used to estimate the causal effect? The default is

`"Wald ratio"`

.- multi_snp_method
Which of the multi-SNP methods to use when there was more than 1 SNPs used to estimate the causal effect? The default is

`"Inverse variance weighted"`

.- group_single_categories
If there are categories with only one outcome, group them together into an "Other" group. The default is

`TRUE`

.- by_category
Separate the results into sections by category? The default is

`TRUE`

.- in_columns
Separate the exposures into different columns. The default is

`FALSE`

.- threshold
p-value threshold to use for colouring points by significance level. If

`NULL`

(default) then colour layer won't be applied.- xlab
x-axis label. If

`in_columns=TRUE`

then the exposure values are appended to the end of`xlab`

. e.g. if`xlab="Effect of"`

then x-labels will read`"Effect of exposure1"`

,`"Effect of exposure2"`

etc. Otherwise will be printed as is.- xlim
limit x-axis range. Provide vector of length 2, with lower and upper bounds. The default is

`NULL`

.- trans
Transformation to apply to x-axis. e.g.

`"identity"`

,`"log2"`

, etc. The default is`"identity"`

.- ao_slc
retrieve sample size and subcategory from

`available_outcomes()`

. If set to`FALSE`

then`mr_res`

must contain the following additional columns:`sample_size`

and`subcategory`

. The default behaviour is to use`available_outcomes()`

to retrieve sample size and subcategory.- priority
Name of category to prioritise at the top of the forest plot. The default is

`"Cardiometabolic"`

.