This function returns response levels for when these are based on
Highest Single Agent (HSA) model.

Response surface methods for drug synergy analysis. Available
methods include generalized and classical Loewe formulations as well as Highest
Single Agent methodology. Response surfaces can be plotted in an interactive
3-D plot and formal statistical tests for presence of synergistic effects are
available. Implemented methods and tests are described in the article
"BIGL: Biochemically Intuitive Generalized Loewe null model for prediction
of the expected combined effect compatible with partial agonism and antagonism"
by Koen Van der Borght, Annelies Tourny, Rytis Bagdziunas, Olivier Thas,
Maxim Nazarov, Heather Turner, Bie Verbist & Hugo Ceulemans (2017)
<doi:10.1038/s41598-017-18068-5>.

Maxim Nazarov

BIGL

Biochemically Intuitive Generalized Loewe Model

hsa function

<dl><dt>doseInput</dt>
<dd>Dose-response dataframe containing <code>"d1"</code> and
<code>"d2"</code> columns</dd>
<dt>parmInput</dt>
<dd>Numeric vector or list with appropriately named
parameter inputs. Typically, it will be coefficients from a
<code>MarginalFit</code> object.</dd>
<dt>...</dt>
<dd>Further arguments that are currently unused</dd></dl>

Arguments

Highest Single Agent model — hsa

<dl>

<dt>doseInput</dt>
<dd>Dose-response dataframe containing <code>"d1"</code> and
<code>"d2"</code> columns</dd>


<dt>parmInput</dt>
<dd>Numeric vector or list with appropriately named
parameter inputs. Typically, it will be coefficients from a
<code>MarginalFit</code> object.</dd>


<dt>...</dt>
<dd>Further arguments that are currently unused</dd>

</dl>

hsa: Highest Single Agent model

Description

Usage

Arguments