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https://github.com/jonocarroll/DFplyr

A `DataFrame` (`S4Vectors`) backend for `dplyr`
https://github.com/jonocarroll/DFplyr

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A `DataFrame` (`S4Vectors`) backend for `dplyr`

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README 

        
---

output: github_document

---



```{r, include = FALSE}

knitr::opts_chunk$set(

    collapse = TRUE,

    comment = "#>",

    fig.path = "man/figures/README-",

    out.width = "100%"

)

```

# DFplyr



The goal of DFplyr is to enable `dplyr` and `ggplot2` support for

`S4Vectors::DataFrame` by providing the appropriate extension methods. As row

names are an important feature of many Bioconductor structures, these are

preserved where possible.



## Installation



You can install the development version from [GitHub](https://github.com/) with:



``` r

# install.packages("devtools")

devtools::install_github("jonocarroll/DFplyr")

```



You can install from [Bioconductor](https://bioconductor.org) with:



``` r

if (!require("BiocManager", quietly =TRUE))

    install.packages("BiocManager")



# The following initializes usage of Bioc devel

BiocManager::install(version='devel')



BiocManager::install("DFplyr")

```



## Examples



First create an S4Vectors `DataFrame`, including S4 columns if desired



```{r}

library(S4Vectors)

m <- mtcars[, c("cyl", "hp", "am", "gear", "disp")]

d <- as(m, "DataFrame")

d$grX <- GenomicRanges::GRanges("chrX", IRanges::IRanges(1:32, width = 10))

d$grY <- GenomicRanges::GRanges("chrY", IRanges::IRanges(1:32, width = 10))

d$nl <- IRanges::NumericList(lapply(d$gear, function(n) round(rnorm(n), 2)))

d

```



This will appear in RStudio's environment pane as a 



```

Formal class DataFrame (dplyr-compatible)

``` 



when using `DFplyr`. No interference with the actual object is required, but

this helps identify that `dplyr`-compatibility is available.



`DataFrame`s can then be used in `dplyr` calls the same as `data.frame` or

`tibble` objects. Support for working with S4 columns is enabled provided they

have appropriate functions. Adding multiple columns will result in the new

columns being created in alphabetical order



```{r}

library(DFplyr)



mutate(d, newvar = cyl + hp)



mutate(d, nl2 = nl * 2)



mutate(d, length_nl = lengths(nl))



mutate(d,

    chr = GenomeInfoDb::seqnames(grX),

    strand_X = BiocGenerics::strand(grX),

    end_X = BiocGenerics::end(grX)

)

```



the object returned remains a standard `DataFrame`, and further calls can be 

piped with `%>%`



```{r}

mutate(d, newvar = cyl + hp) %>%

    pull(newvar)

```



Some of the variants of the `dplyr` verbs also work



```{r}

mutate_if(d, is.numeric, ~ .^2)



mutate_if(d, ~ inherits(., "GRanges"), BiocGenerics::start)

```



Use of `tidyselect` helpers is limited to within `dplyr::vars()` calls and using 

the `_at` variants



```{r}

mutate_at(d, vars(starts_with("c")), ~ .^2)



select_at(d, vars(starts_with("gr")))

```



Importantly, grouped operations are supported. `DataFrame` does not 

natively support groups (the same way that `data.frame` does not) so these

are implemented specifically for `DFplyr`



```{r}

group_by(d, cyl, am)

```



Other verbs are similarly implemented, and preserve row names where possible



```{r}

select(d, am, cyl)



arrange(d, desc(hp))



filter(d, am == 0)



slice(d, 3:6)



group_by(d, gear) %>%

    slice(1:2)

```



`rename` is itself renamed to `rename2` due to conflicts between {dplyr} and 

{S4Vectors}, but works in the {dplyr} sense of taking `new = old` replacements 

with NSE syntax



```{r}

select(d, am, cyl) %>%

    rename2(foo = am)

```



Row names are not preserved when there may be duplicates or they don't make

sense, otherwise the first label (according to the current de-duplication

method, in the case of `distinct`, this is via `BiocGenerics::duplicated`). This

may have complications for S4 columns.



```{r}

distinct(d)



group_by(d, cyl, am) %>%

    tally(gear)



count(d, gear, am, cyl)

```



## Coverage



Most `dplyr` functions are implemented with the exception of `join`s. 



If you find any which are not, please [file an issue](https://github.com/jonocarroll/DFplyr/issues/new).