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# VarExp
VarExp
======
The R package **VarExp** provides functions for the estimating of the percentage of phenotypic variance explained by genetic effects, interaction effects or jointly by both effects. This suite of functions are useful for meta-analysis designs where pooling individual genotype data is challenging. A pre-print article related to this work is available [here](bioRkiv link)
The R package **VarExp** provides functions for the estimating of the
percentage of phenotypic variance explained by genetic effects,
interaction effects or jointly by both effects. This suite of functions
are useful for meta-analysis designs where pooling individual genotype
data is challenging. A pre-print article related to this work is
available [here](bioRkiv%20link)
## Prerequisite
Prerequisite
------------
Library [**Rcurl**](https://cran.r-project.org/web/packages/RCurl/index.html) is required to run **VarExp**
Library
[**Rcurl**](https://cran.r-project.org/web/packages/RCurl/index.html) is
required to run **VarExp**
## Installation
Installation
------------
For now, **VarExp** can be installed only using package source. In R, after setting your working directory to *VarExp_0.1.0.tar.gz* location, type:
For now, **VarExp** can be installed only using package source. In R,
after setting your working directory to *VarExp\_0.1.0.tar.gz* location,
type:
``` r
install.packages("VarExp_0.1.0.tar.gz", repos = NULL, type = "source")
```
## Input format
Input format
------------
Two input files are required.
* A file providing the meta-analysis results with the following mandatory columns:
+ the rs identifier of the variant
+ the chromosome number on which the variant is
+ the physical position of the variant (currently in NCBI Build B37)
+ the tested allele of the variant
+ the frequency of the allele A0
+ the regression coefficient of the main genetic effect
+ the regression coefficient of the interaction effect
```{r, echo = FALSE}
data("GWAS")
print(GWAS, row.names = FALSE)
```
* A file providing the summary statistics for the outcome and the exposure in each individual cohort included in the meta-analysis.
- A file providing the meta-analysis results with the following
mandatory columns:
- the rs identifier of the variant
- the chromosome number on which the variant is
- the physical position of the variant (currently in NCBI Build
B37)
- the tested allele of the variant
- the frequency of the allele A0
- the regression coefficient of the main genetic effect
- the regression coefficient of the interaction effect
<!-- -->
## RSID CHR POS A0 FREQ_A0 MAIN_EFFECT INT_EFFECT
## rs72900467 1 989500 A 0.05558 -0.282895628 0.11487230
## rs34372380 1 1305201 T 0.11205 -0.003162676 0.01704444
## rs4422949 1 834928 G 0.21753 -0.133573045 -0.11129018
## rs9442366 1 1009234 T 0.42201 0.121852094 -0.09421119
## rs61768199 1 781845 G 0.09736 -0.017142010 0.02977832
## rs9439462 1 1462766 T 0.04784 0.206595425 0.06823945
## rs307370 1 1273278 A 0.16546 0.052140346 -0.01852352
## rs11807848 1 1061166 C 0.39556 0.169484484 0.03845663
## rs7538305 1 824398 C 0.15379 0.054950590 -0.04494799
## rs28613513 1 1112810 T 0.05358 -0.001334013 0.10294423
- A file providing the summary statistics for the outcome and the
exposure in each individual cohort included in the meta-analysis.
Mandatory columns of this file are:
+ the identifier of the cohort
+ the sample size of the cohort
+ the phenotype mean in the cohort
+ the standard deviation of the phenotype in the cohort
+ the exposure mean in the cohort
+ the standard deviation of the exposure in the cohort
- the identifier of the cohort
- the sample size of the cohort
- the phenotype mean in the cohort
- the standard deviation of the phenotype in the cohort
- the exposure mean in the cohort
- the standard deviation of the exposure in the cohort
``` {r, echo = FALSE}
data("COHORT")
print(COHORT, row.names = FALSE)
```
<!-- -->
Note that in the case of a binary exposure, the two latter columns can be replaced by a single column providing the count of exposed individuals in each cohort.
## Cohort PHENO_N PHENO_Mean PHENO_SD EXPO_Mean EXPO_SD
## 1 10000 1.297265 3.097524 2.002715 1.250979
## 2 10000 1.288332 3.152367 2.009427 1.242574
## 3 10000 1.390218 3.109720 1.995473 1.258670
## 4 10000 1.342020 3.151429 1.999943 1.256718
## 5 10000 1.385564 3.153274 2.002401 1.235129
## Short tutorial
Note that in the case of a binary exposure, the two latter columns can
be replaced by a single column providing the count of exposed
individuals in each cohort.
Short tutorial
--------------
Data used in this tutorial are included in the ***VarExp*** package.
``` r
# Load the package
library(VarExp)
......@@ -82,16 +111,22 @@ std_betaI <- standardizeBeta(GWAS$MAIN_EFFECT, GWAS$INT_EFFECT, GWAS$FREQ_A0, pa
fracG <- calculateVarFrac(std_betaG, std_betaI, C, parsY[2], sum(COHORT$PHENO_N), "G")
fracI <- calculateVarFrac(std_betaG, std_betaI, C, parsY[2], sum(COHORT$PHENO_N), "I")
fracJ <- calculateVarFrac(std_betaG, std_betaI, C, parsY[2], sum(COHORT$PHENO_N), "J")
```
## Bug report / Help
Bug report / Help
-----------------
Please open an issue if you find a bug.
## Code of conduct
Code of conduct
---------------
Please note that this project is released with a [Contributor Code of Conduct](https://gitlab.pasteur.fr/statistical-genetics/VarExp/blob/master/code-of-conduct.md). By participating in this project you agree to abide by its terms.
Please note that this project is released with a [Contributor Code of
Conduct](https://gitlab.pasteur.fr/statistical-genetics/VarExp/blob/master/code-of-conduct.md).
By participating in this project you agree to abide by its terms.
## License
License
-------
This project is licensed under the MIT License - see the [LICENSE.md](https://gitlab.pasteur.fr/statistical-genetics/VarExp/blob/master/LICENSE) file for details
\ No newline at end of file
This project is licensed under the MIT License - see the
[LICENSE.md](https://gitlab.pasteur.fr/statistical-genetics/VarExp/blob/master/LICENSE)
file for details
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