---
title: "CoPheScan: Input data"
author: "Ichcha Manipur"
date: "`r Sys.Date()`"
output: rmarkdown::html_vignette
vignette: >
  %\VignetteIndexEntry{CoPheScan: Input data}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
---

```{r, include = FALSE}
knitr::opts_chunk$set(
	collapse = TRUE,
	comment = "#>",
	fig.path = "Input-"
)
```

The input dataset for a trait (querytrait) should contain the summary data for SNPs in a genomic region around the query variant (querysnpid) and should have the following fields:

**For a Case-control dataset**

beta: $\beta$ or effect size

varbeta: variance of $\beta$ or square of the standard error of $\beta$

snp: SNP identifier which maybe rsid or CHR_BP_REF_ALT or CHR_BP

type:'cc'

N: sample size

**For a Quantitative dataset**

When, beta and varbeta are not available the following

beta: $\beta$ or effect size

varbeta: variance of $\beta$ or square of the standard error of $\beta$

snp: SNP identifier which maybe rsid or CHR_BP_REF_ALT or CHR_BP

type:'quant'

N: sample size

sdY: for a quantitative trait, the population standard deviation of the trait.

**Additional fields in case of missing beta/varbeta or sdY**

MAF: Minor allele frequency (only required when either beta/varbeta or sdY are unavailable)

pvalues: only required when beta/varbeta are unavailable

s: fraction of samples that are cases (only for a case-control trait when beta/varbeta are unavailable)

```{r warning=FALSE, message=FALSE}
library(cophescan)
```

Explore the data structure of the example dataset available in the cophescan package

```{r warning=FALSE, message=FALSE}
data("cophe_multi_trait_data")
trait_dat = cophe_multi_trait_data$summ_stat$Trait_1
str(trait_dat)
```

**Additional field for `cophe.susie`**

LD: Linkage Disequilibrium matrix with row and column names being the same as the snp field.

```{r}
trait_dat$LD = cophe_multi_trait_data$LD
str(trait_dat$LD[1:10, 1:10])
```

It is important to check that there is alignment of alleles for which the beta is reported and those in the LD matrix.
This can be verified either using coloc::check_alignment or performing a diagnostic check using the susie package <https://stephenslab.github.io/susieR/articles/susierss_diagnostic.html>.

**Note**

-   The input summary data structure for a trait is the same format as required by coloc. To gain a detailed understanding of the input please see the coloc vignette <https://chr1swallace.github.io/coloc/articles/a02_data.html> and the test datasets provided with the coloc package.
-   More information on the input can be obtained from the coloc documentation : `?coloc::check_dataset`

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