Type:	Package
Title:	Ordered Panel
Version:	0.1.1
Date:	2026-03-18
Description:	The ordered panel methodology (Zezulinski et al 2025 <doi:10.1159/000545366>) provides a structured framework for identifying and organizing sets of biomarkers, such as genetic variants, that distinguish between positive and negative subjects in a study when only a training cohort is available. This approach is particularly useful in situations where an independent validation cohort does not yet exist, rendering conventional performance metrics such as the receiver operating characteristic (ROC) curve and area under the ROC curve (AUC) inappropriate or potentially misleading. The methodology emphasizes transparent construction and evaluation of ordered signatures of biomarkers, allowing investigators to examine operating characteristics without establishing predictive performance.
License:	GPL-2
Encoding:	UTF-8
Language:	en-US
RoxygenNote:	7.3.3
LazyData:	true
LazyDataCompression:	xz
URL:	https://github.com/tingtingzhan/ordPanel, https://tingtingzhan-ordpanel.netlify.app
Depends:	R (≥ 4.5.0)
Imports:	cli, flextable, ggplot2, methods, consort, patchwork, scales
Suggests:	testthat (≥ 3.0.0)
Config/testthat/edition:	3
NeedsCompilation:	no
Packaged:	2026-03-18 21:21:07 UTC; tingtingzhan
Author:	Tingting Zhan [aut, cre], Aejaz Sayeed [ctb]
Maintainer:	Tingting Zhan <tingtingzhan@gmail.com>
Repository:	CRAN
Date/Publication:	2026-03-19 07:20:02 UTC

ordPanel: Ordered Panel

Description

The ordered panel methodology (Zezulinski et al 2025 doi:10.1159/000545366) provides a structured framework for identifying and organizing sets of biomarkers, such as genetic variants, that distinguish between positive and negative subjects in a study when only a training cohort is available. This approach is particularly useful in situations where an independent validation cohort does not yet exist, rendering conventional performance metrics such as the receiver operating characteristic (ROC) curve and area under the ROC curve (AUC) inappropriate or potentially misleading. The methodology emphasizes transparent construction and evaluation of ordered signatures of biomarkers, allowing investigators to examine operating characteristics without establishing predictive performance.

Author(s)

Maintainer: Tingting Zhan tingtingzhan@gmail.com (ORCID)

Other contributors:

• Aejaz Sayeed (ORCID) [contributor]

See Also

Useful links:

• https://github.com/tingtingzhan/ordPanel

• https://tingtingzhan-ordpanel.netlify.app

Extract Rows of panel

Description

Extract Rows of panel

Usage

## S3 method for class 'panel'
x[i, ...]

Arguments

Value

The S3 method ⁠[.panel()⁠ returns a panel.

Visualize panellist using Package ggplot2

Description

Visualize panellist using Package ggplot2

Usage

## S3 method for class 'panellist'
autoplot(object, ...)

## S3 method for class 'panellist'
autolayer(object, which = c("oc", "roc"), ...)

Arguments

Value

The S3 method autoplot.panellist() returns a ggplot object.

S4 Class panel

Description

S4 Class panel

Usage

panel(m1 = zezulinski1, m0 = zezulinski0)

Arguments

Value

The function panel() returns an R object of S4 class panel.

Slots

m1,m0

logical matrix-es, true and false positives, respectively. In other words, the variants tested positive in the positive and negative subjects (patients), respectively. Rows are different variants. Columns are different subjects. The rownames of m0 and m1 must be the same.

id

list of character vectors

ordered

logical scalar, whether this is an ordered panel

label

(optional) character scalar, a human-friendly description of the panel

consort

(optional) data.frame to create a consort_plot

panellist

Description

To combine multiple panels.

Usage

panellist(...)

Arguments

Value

The function panellist() returns an S3 object of panellist, which inherits from the classes listof and list.

Data Sets in Package ordPanel

Description

Data sets used as examples in package ordPanel.

Usage

zezulinski1

zezulinski0

Format

An object of class matrix (inherits from array) with 12877 rows and 50 columns.

An object of class matrix (inherits from array) with 12877 rows and 31 columns.

References

doi:10.1159/000545366

Flow-Chart of Ordered panel

Description

To create a flow-chart for the creation of an ordered panel.

Usage

## S3 method for class 'panel'
plot(x, ...)

Arguments

Value

The function plot.panel() returns

• an R object of class 'consort' (returned from the function consort_plot), if the input panel has a non-default ⁠@consort⁠ slot;

• an invisible NULL-value, if the input panel has a default ⁠@consort⁠ slot.

Flow-Charts of Ordered panellist

Description

To create flow-charts for the creation of an ordered panellist.

Usage

## S3 method for class 'panellist'
plot(x, ...)

Arguments

Value

The function plot.panellist() returns

• a patchwork, (returned from the function wrap_plots), if the input panellist has at least one panel with a non-default ⁠@consort⁠ slot;

• an invisible NULL-value, if all panels in the input panellist have a default ⁠@consort⁠ slot.

Show panel

Description

Show panel

Usage

## S4 method for signature 'panel'
show(object)

Arguments

Value

The show method of panel class does not have a returned value.

Sort panel by Given Criterion

Description

To sort a panel by some given criterion.

Usage

## S3 method for class 'panel'
sort_by(x, y, ...)

Arguments

Value

The S3 method sort_by.panel() returns an ordered panel.

Select a subset of panel

Description

Select a subset of panel

Usage

## S3 method for class 'panel'
subset(x, subset, append.label = FALSE, ...)

Arguments

Value

The S3 method subset.panel() returns an R object of S4 class panel.

Number of True & False Positives

Description

Number of True & False Positives

Usage

sum1(x)

sum0(x)

cumsum1(x)

cumsum0(x)

Arguments

Value

The functions sum1() and sum0() return a integer vector.

The functions cumsum1() and cumsum0() return a non-decreasing integer vector.