Introduction
The AnimalGene2QTL
provides an interface to retrieve QTL data ,
gene data , SNP data.The package enables retrieval of large amounts
of data in a uniform way without the need to know the underlying
database schemas or write complex SQL queries.
Quick start
Viewing AnimalGene2QTL dataset
Every analysis with AnimalGene2QTL
starts with Viewing a
AnimalGene2QTL
dataset to use.
The function listQTL will display all available QTL dataset.
```{r eval=TRUE} library(AnimalGene2QTL) listQTL()
## `How to build a QTL query`
The `getAnimalQTL` function has six arguments that need to be
introduced:
*gene_filters*, *qtl_attributes*, *gene_values*, *data_set*
, *snp*, *snp_attributes*.
* **gene_filters**: define a restriction on the query.
For example you want to restrict the output to all QTL located
on the human X chromosome
then the `gene_filters`:`chromosome_name` can be used with gene
values `X`.
The `listGeneAF` function displays all available gene filters
in the selected dataset.
* **qtl_attributes**: define the values we are interested in to retrieve.
For example we want to retrieve the QTL ID or QTL name.
The `listQTLAF` function displays all available QTL attributes
in the selected dataset.
* **gene_values**: The input gene data.
* **data_set**: There are five numbers:1,2,3,4,5.`listQTL`function display
which to input.
* **snp**: default FALSE,when it is TRUE,that mean retrieve SNP.
* **snp_attributes**: input the attribute of SNP what to retrieve,`listSNPattributes`function display it.
```{r eval=TRUE}
attributes <- listQTLAF()
head(attributes)
filters <- listGeneAF(1)
head(filters)
getAnimalQTL() function
The getAnimalQTL
function is the main query function in
AnimalGene2QTL
.
It has four main arguments.
Now that we selected a AnimalGene2QTL
dataset, and know
about qtl_attributes
,
gene_filters
, and the gene_values
for gene_filters
;
we can build a AnimalGene2QTL
query. Let us make an easy query for the following problem:
We have a list of gene identifiers from the Ensembl and we
want to retrieve the QTL identifiers.
Let us now run the query:
```{r eval=TRUE} geneid <- c("ENSBTAG00000009851", "ENSBTAG00000005101", "ENSBTAG00000036262") qtl <- getAnimalQTL(qtl_attributes=c('QTL_ID'),gene_filters='ensembl_gene_id' ,gene_values=geneid,data_set=1); head(qtl);
## `Examples of AnimalGene2QTL queries`
In the sections below a variety of example
queries are described.
Every example is written
as a task, and we have to come up with a `AnimalGene2QTL`
solution to the problem.
### `Task 1: Retrieve all identifiers of genes by QTL`
`identifiers:"64577","2199","2354"`
```{r eval=TRUE}
qtlid <- c("64577","2199","2354");
gene <- getAnimalGene(gene_attributes="ensembl_gene_id",qtl_filters=c("QTL_ID")
,qtl_values=qtlid, data_set=2);
head(gene)
Task 2: Retrieve all identifiers of SNP by QTL
identifiers:"4097"
{r eval=TRUE}
snp <- getSNPbyQTL('refsnp_id','QTL_ID','4097',2);
head(snp)
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