load_input_and_run_cape

This function loads the input file path and runs cape
It is used to run CAPE from a non R script (python)

Combined Analysis of Pleiotropy and Epistasis infers predictive
networks between genetic variants and phenotypes. It can be used with
standard two-parent populations as well as multi-parent populations, such
as the Diversity Outbred (DO) mice, Collaborative Cross (CC) mice, or the
multi-parent advanced generation intercross (MAGIC) population of Arabidopsis
thaliana. It uses complementary information of pleiotropic gene variants across
different phenotypes to resolve models of epistatic interactions between alleles.
To do this, cape reparametrizes main effect and interaction coefficients from
pairwise variant regressions into directed influence parameters. These
parameters describe how alleles influence each other, in terms of suppression
and enhancement, as well as how gene variants influence phenotypes. All of the
final interactions are reported as directed interactions between pairs of
parental alleles. For detailed descriptions of the methods used in this package
please see the following references.
Carter, G. W., Hays, M., Sherman, A. & Galitski, T. (2012) <doi:10.1371/journal.pgen.1003010>.
Tyler, A. L., Lu, W., Hendrick, J. J., Philip, V. M. & Carter, G. W. (2013) <doi:10.1371/journal.pcbi.1003270>.

Anna L Tyler

cape

Combined Analysis of Pleiotropy and Epistasis for Diversity
Outbred Mice

Anna Tyler

Jake Emerson

Baha El Kassaby

Ann Wells

Georgi Kolishovski

Vivek Philip

Gregory Carter

load_input_and_run_cape function

<dl><dt>input_file</dt>
<dd>data input to be loaded</dd>
<dt>yaml_params</dt>
<dd>a parameter set up in the form of a YAML string</dd>
<dt>results_path</dt>
<dd>path to the results</dd>
<dt>run_parallel</dt>
<dd>boolean, if TRUE runs certain parts of the code as parallel blocks</dd>
<dt>results_file</dt>
<dd>the name of the saved data_obj RDS file. The base name is used as the base name for all saved RDS files.</dd>
<dt>p_or_q</dt>
<dd>A threshold indicating the maximum adjusted p value considered</dd>
<dt>n_cores</dt>
<dd>integer, default is 4</dd>
<dt>initialize_only</dt>
<dd>boolean, default: FALSE</dd>
<dt>verbose</dt>
<dd>boolean, output goes to stdout</dd>
<dt>param_file</dt>
<dd>path to yml parameter file for running cape</dd>
<dt>create_report</dt>
<dd>boolean, if true we create the corresponding HTML report page</dd>
<dt>qtl_id_col</dt>
<dd>argument for read_population, an optional column number for individual IDs</dd>
<dt>qtl_na_strings</dt>
<dd>argument for read_population, an optional string for missing values</dd></dl>

Arguments

Loads input and run CAPE — load_input_and_run_cape

<dl>

<dt>input_file</dt>
<dd>data input to be loaded</dd>


<dt>yaml_params</dt>
<dd>a parameter set up in the form of a YAML string</dd>


<dt>results_path</dt>
<dd>path to the results</dd>


<dt>run_parallel</dt>
<dd>boolean, if TRUE runs certain parts of the code as parallel blocks</dd>


<dt>results_file</dt>
<dd>the name of the saved data_obj RDS file. The base name is used as the base name for all saved RDS files.</dd>


<dt>p_or_q</dt>
<dd>A threshold indicating the maximum adjusted p value considered</dd>


<dt>n_cores</dt>
<dd>integer, default is 4</dd>


<dt>initialize_only</dt>
<dd>boolean, default: FALSE</dd>


<dt>verbose</dt>
<dd>boolean, output goes to stdout</dd>


<dt>param_file</dt>
<dd>path to yml parameter file for running cape</dd>


<dt>create_report</dt>
<dd>boolean, if true we create the corresponding HTML report page</dd>


<dt>qtl_id_col</dt>
<dd>argument for read_population, an optional column number for individual IDs</dd>


<dt>qtl_na_strings</dt>
<dd>argument for read_population, an optional string for missing values</dd>

</dl>

load_input_and_run_cape: Loads input and run CAPE

Description

Usage

Arguments