# planet <img src="man/figures/logo.png" align="right" height = "139" />
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`planet` is an R package for inferring **ethnicity** (1), **gestational
age** (2), and **cell composition** (3) from placental DNA methylation
data.
See full documentation at <https://victor.rbind.io/planet>
### Installation
You can install `planet` from this github repo:
``` r
devtools::install_github('wvictor14/planet')
```
### Usage
See [vignettes](https://victor.rbind.io/planet/articles) for more
detailed usage.
#### Example Data
All functions in this package take as input DNAm data the 450k and EPIC
DNAm microarray. For best performance I suggest providing unfiltered
data normalized with noob and BMIQ. A processed example dataset,
`plBetas`, is provided to show the format that this data should be in.
The output of all `planet` functions is a `data.frame`.
A quick example of each major function is illustrated with this example
data:
``` r
library(minfi)
library(planet)
#load example data
data(plBetas)
data(plPhenoData) # sample information
```
#### Predict Ethnicity
``` r
predictEthnicity(plBetas) %>%
head()
#> 1860 of 1860 predictors present.
#> # A tibble: 6 x 7
#> Sample_ID Predicted_ethni~ Predicted_ethni~ Prob_African Prob_Asian
#> <chr> <chr> <chr> <dbl> <dbl>
#> 1 GSM19449~ Caucasian Caucasian 0.00331 0.0164
#> 2 GSM19449~ Caucasian Caucasian 0.000772 0.000514
#> 3 GSM19449~ Caucasian Caucasian 0.000806 0.000699
#> 4 GSM19449~ Caucasian Caucasian 0.000883 0.000792
#> 5 GSM19449~ Caucasian Caucasian 0.000885 0.00130
#> 6 GSM19449~ Caucasian Caucasian 0.000852 0.000973
#> # ... with 2 more variables: Prob_Caucasian <dbl>, Highest_Prob <dbl>
```
#### Predict Gestational Age
There are 3 gestational age clocks for placental DNA methylation data
from Lee Y. et al. 2019 (2). To use a specific one, we can use the
`type` argument in `predictAge`:
``` r
predictAge(plBetas, type = 'RPC') %>%
head()
#> 558 of 558 predictors present.
#> [1] 38.46528 33.09680 34.32520 35.50937 37.63910 36.77051
```
#### Predict Cell Composition
Reference data to infer cell composition on placental villi DNAm samples
(3) can be used with cell deconvolution from minfi or EpiDISH. These are
provided in this package as `plCellCpGsThird` and `plCellCpGsFirst` for
third trimester (term) and first trimester samples, respectively.
``` r
data('plCellCpGsThird')
minfi:::projectCellType(
# subset your data to cell cpgs
plBetas[rownames(plCellCpGsThird),],
# input the reference cpg matrix
plCellCpGsThird,
lessThanOne = FALSE) %>%
head()
#> Trophoblasts Stromal Hofbauer Endothelial nRBC
#> GSM1944936 0.1091279 0.04891919 0.000000e+00 0.08983998 0.05294062
#> GSM1944939 0.2299918 0.00000000 -1.806592e-19 0.07888007 0.03374149
#> GSM1944942 0.1934287 0.03483540 0.000000e+00 0.09260353 0.02929310
#> GSM1944944 0.2239896 0.06249135 1.608645e-03 0.11040693 0.04447951
#> GSM1944946 0.1894152 0.07935955 0.000000e+00 0.10587439 0.05407587
#> GSM1944948 0.2045124 0.07657717 0.000000e+00 0.09871149 0.02269798
#> Syncytiotrophoblast
#> GSM1944936 0.6979477
#> GSM1944939 0.6377822
#> GSM1944942 0.6350506
#> GSM1944944 0.5467642
#> GSM1944946 0.6022329
#> GSM1944948 0.6085825
```
### References
1. [**Yuan V**, Price EM, Del Gobbo G, Mostafavi S, Cox B, Binder AM,
et al. Accurate ethnicity prediction from placental DNA methylation
data. Epigenetics & Chromatin. 2019 Aug
9;12(1):51.](https://epigeneticsandchromatin.biomedcentral.com/articles/10.1186/s13072-019-0296-3)
2. [Lee Y, Choufani S, Weksberg R, Wilson SL, **Yuan V**, et
al. Placental epigenetic clocks: estimating gestational age using
placental DNA methylation levels. Aging (Albany NY).
2019;11(12):4238–4253.
doi:10.18632/aging.102049](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6628997/)
3. [**Yuan V**, Hui D, Yin Y, Peñaherrera MS, Beristain AG, Robinson
WP. Cell-specific characterization of the placental methylome. BMC
Genomics. 2021 Jan
6;22(1):6.](https://bmcgenomics.biomedcentral.com/articles/10.1186/s12864-020-07186-6)
