Covariates

<p>Artificial data set with 2 covariates across 15 samples. 
    Columns of the file must match to those of the 
    expression and genotype data sets.</p>

datasets

Matrix eQTL is designed for fast eQTL analysis on large datasets.
Matrix eQTL can test for association between genotype
and gene expression using linear regression
with either additive or ANOVA genotype effects.
The models can include covariates to account for factors
as population stratification, gender, and clinical variables.
It also supports models with heteroscedastic and/or correlated errors,
false discovery rate estimation and
separate treatment of local (cis) and distant (trans) eQTLs.
For more details see Shabalin (2012) <doi:10.1093/bioinformatics/bts163>.

Andrey A Shabalin

MatrixEQTL

Matrix eQTL: Ultra Fast eQTL Analysis via Large Matrix
Operations

Covariates function

<p></p><table><tr><td>
        id     </td>
<td> Sam_01   </td>
<td> Sam_02 </td>
<td> &#8230; </td>
</tr><tr><td>
        gender </td>
<td> 0        </td>
<td> 0      </td>
<td> &#8230; </td>
</tr><tr><td>
        age    </td>
<td> 40       </td>
<td> 46     </td>
<td> &#8230; </td>
</tr></table>

Covariates: Artificial data for Matrix eQTL sample code: Covariates.

Description

Arguments

Format

References

See Also