mendelianrandomization.Rmd

---
title: "Eicosanoids mediators of hypertension: gwas"
author: "Joonatan Palmu"
date: "`r format(Sys.time(), '%d.%m.%Y')`"
---


```{r options, include=FALSE}
knitr::opts_chunk$set(include = TRUE, echo = TRUE, message = FALSE,
                      results='asis', cache=FALSE, warning=FALSE)
options(knitr.kable.NA = "")
now <- format(Sys.time(), '%Y%m%d-%H%M%S')
```

```{r Remove temporary data, include = FALSE}
unlink("cache", recursive=TRUE)
dir.create("cache", showWarnings = FALSE)
dir.create("report", showWarnings = FALSE)
```

# Libraries

<details>
  <summary>Open/Close</summary>

```{r libraries, results = 'hide'}
library(knitr)
library(tidyr)
library(broom)
library(readr)
library(dplyr)
library(purrr)
library(parallel)
library(data.table)
library(TwoSampleMR)
```

</details>

```{r download outcomes}
ao <- available_outcomes() 
```

```{r select traits}
traits <- ao %>% filter(grepl("Systolic blood pressure", trait)) %>%
    arrange(desc(sample_size))
```

```{r traits}
traits %>%
    select(id, trait, consortium, author, sample_size) %>%
    kable
```


```{r test}
exposure_dat <- read_exposure_data(
    filename = 'eicgwas.csv',
    sep = ',',
    snp_col = 'snip',
    beta_col = 'frequentist_add_beta_1',
    se_col = 'frequentist_add_se_1',
    effect_allele_col = 'alleleA',
    phenotype_col = 'Phenotype',
    units_col = 'units',
    other_allele_col = 'alleleB',
    eaf_col = 'all_maf',
    samplesize_col = 'samplesize',
    ncase_col = 'ncase',
    ncontrol_col = 'ncontrol',
    gene_col = 'gene',
    pval_col = 'frequentist_add_pvalue')

exposure_dat

%>%
    clump_data
```

```{r Exposures}
exposure_dat %>%
    select(SNP,
           chr.exposure,
           effect_allele.exposure,
           other_allele.exposure,
           eaf.exposure,
           beta.exposure,
           se.exposure,
           pval.exposure,
           chr.exposure) %>%
    mutate(pval.exposure = sprintf("%.1e", pval.exposure),
           chr.exposure = sprintf("%i", chr.exposure)) %>%
    mutate_if(is.numeric, round, 3) %>%
    kable
```

```{r analysis}
outcome_dat <- extract_outcome_data(exposure_dat$SNP,
                                    traits$id[1],
                                    traits$id,
                                    proxies = 1,
                                    rsq = 0.8,
                                    align_alleles = 1,
                                    palindromes = 1,
                                    maf_threshold = 0.3)

dat <- harmonise_data(exposure_dat, outcome_dat, action = 2)

mr_results <- mr(dat,  method_list = c("mr_simple_mode",
                                       "mr_egger_regression",
                                       "mr_weighted_median",
                                       "mr_ivw",
                                       "mr_weighted_mode"))
```

```{r mrbase results}
mr_results %>%
    dplyr::mutate(qval = p.adjust(pval, method="BH")) %>%
    arrange(pval) %>%
    select(method, b, pval, qval) %>%
    mutate_if(is.numeric, round, 3) %>%
    kable
```