From 798df15f8ac4a4039465750c39e023c5659cb221 Mon Sep 17 00:00:00 2001 From: Kevin Rue-Albrecht Date: Mon, 25 Sep 2023 13:44:24 +0100 Subject: [PATCH] Built site for gh-pages --- .nojekyll | 2 +- index.html | 4 ++-- intro.html | 10 +++++----- search.json | 8 ++++---- ui.html | 37 ++++++++++++++++++------------------- 5 files changed, 30 insertions(+), 31 deletions(-) diff --git a/.nojekyll b/.nojekyll index 63a6717..5075e85 100644 --- a/.nojekyll +++ b/.nojekyll @@ -1 +1 @@ -3998fe11 \ No newline at end of file +c860c805 \ No newline at end of file diff --git a/index.html b/index.html index c408e67..7936e79 100644 --- a/index.html +++ b/index.html @@ -195,8 +195,8 @@

Preface

This book caters for three main groups of users:

See Rue-Albrecht et al. (2018) for the original publication.

diff --git a/intro.html b/intro.html index 8ab39e7..b617ccf 100644 --- a/intro.html +++ b/intro.html @@ -151,22 +151,22 @@

1  Figure 2.1).

+

iSEE is a Bioconductor package designed to produce interactive web applications for the visualisation of biological assays (Figure 2.1).

-
Figure 1.1: The iSEE app interface.
+
Figure 1.1: The iSEE app interface, for an example data set.
-

Initiated in 2017 with single-cell RNA-sequencing in mind, iSEE was designed in such a way that it naturally handles any biological assay that can be stored in a rectangular matrix of features (in rows) and samples (in columns).

-

What makes iSEE stand out from other interactive web-application is its focus on the SummarizedExperiment class (Figure 1.2), a data structure is widely used throughout the Bioconductor project, from bulk to single-cell experiments.

+

Initiated in 2017 with single-cell RNA-sequencing in mind, iSEE was designed in such a way that it naturally handles any biological assay that can be stored in a rectangular matrix of features (in rows) and samples (in columns).

+

What makes iSEE stand out from other interactive web-application is its focus on the SummarizedExperiment class (Figure 1.2), a data structure that is widely used throughout the Bioconductor project, from bulk to single-cell experiments.

Figure 1.2: Schematic representation of the SummarizedExperiment class (reproduced from the vignette of the SummarizedExperiment package).
-

The well-defined and stable SummarizedExperiment data structure makes it easy for iSEE to automatically detect information commonly stored in dedicated components of SummarizedExperiment objects and display that information in a range of interactive panels, including tables and plots.

+

The well-defined and stable SummarizedExperiment data structure makes it easy for iSEE to automatically detect information commonly stored in dedicated components of SummarizedExperiment objects and display that information in a range of interactive panels, including tables and plots.

diff --git a/search.json b/search.json index dab0df8..0100c97 100644 --- a/search.json +++ b/search.json @@ -11,7 +11,7 @@ "href": "intro.html", "title": "1  Introduction", "section": "", - "text": "iSEE is a Bioconductor package designed to produce interactive web applications for the visualisation of biological assays (Figure 2.1).\n\n\n\nFigure 1.1: The iSEE app interface.\n\n\nInitiated in 2017 with single-cell RNA-sequencing in mind, iSEE was designed in such a way that it naturally handles any biological assay that can be stored in a rectangular matrix of features (in rows) and samples (in columns).\nWhat makes iSEE stand out from other interactive web-application is its focus on the SummarizedExperiment class (Figure 1.2), a data structure is widely used throughout the Bioconductor project, from bulk to single-cell experiments.\n\n\n\nFigure 1.2: Schematic representation of the SummarizedExperiment class (reproduced from the vignette of the SummarizedExperiment package).\n\n\nThe well-defined and stable SummarizedExperiment data structure makes it easy for iSEE to automatically detect information commonly stored in dedicated components of SummarizedExperiment objects and display that information in a range of interactive panels, including tables and plots." + "text": "iSEE is a Bioconductor package designed to produce interactive web applications for the visualisation of biological assays (Figure 2.1).\n\n\n\nFigure 1.1: The iSEE app interface, for an example data set.\n\n\nInitiated in 2017 with single-cell RNA-sequencing in mind, iSEE was designed in such a way that it naturally handles any biological assay that can be stored in a rectangular matrix of features (in rows) and samples (in columns).\nWhat makes iSEE stand out from other interactive web-application is its focus on the SummarizedExperiment class (Figure 1.2), a data structure that is widely used throughout the Bioconductor project, from bulk to single-cell experiments.\n\n\n\nFigure 1.2: Schematic representation of the SummarizedExperiment class (reproduced from the vignette of the SummarizedExperiment package).\n\n\nThe well-defined and stable SummarizedExperiment data structure makes it easy for iSEE to automatically detect information commonly stored in dedicated components of SummarizedExperiment objects and display that information in a range of interactive panels, including tables and plots." }, { "objectID": "ui.html#overview", @@ -25,21 +25,21 @@ "href": "ui.html#panels", "title": "2  The user interface", "section": "2.2 Panels", - "text": "2.2 Panels\nUnder entirely default settings, data sets loaded into the iSEE app are automatically parsed for standard information stored in SummarizedExperiment objects. Based on the information available and a set of eight core panel types designed to display different pieces of information, the iSEE() function automatically populates the interface with one panel of each type for which the relevant information is available.\n\n\n\nFigure 2.1: First row of panel in the iSEE app interface, for an example data set.\n\n\nThe example code given in the help page of the iSEE() function produces an iSEE app that showcases all eight core panel types:\n\n\n\n\n\n\n\n(a) Reduced dimension plot\n\n\n\n\n\n\n\n(b) Row data table\n\n\n\n\n\n\n\n(c) Feature assay plot\n\n\n\n\n\n\n\n\n\n(d) Column data plot\n\n\n\n\n\n\n\n(e) Row data plot\n\n\n\n\n\n\n\n(f) Sample assay plot\n\n\n\n\n\n\n\n\n\n(g) Column data table\n\n\n\n\n\n\n\n(h) Complex heatmap plot\n\n\n\n\nFigure 2.2: Core panel types in the iSEE package, in their default configuration.\n\n\nEach core panel type is designed to display a different piece of information stored in the object. The purpose of each panel will be discussed in a separate chapter." + "text": "2.2 Panels\nUnder entirely default settings, data sets loaded into the iSEE app are automatically parsed for standard information stored in SummarizedExperiment objects. Based on the information available and a set of eight core panel types designed to display different pieces of information, the iSEE() function automatically populates the interface with one panel of each type for which the relevant information is available.\n\n\n\nFigure 2.1: First row of panel in the iSEE app interface, for an example data set.\n\n\nThe example code given in the help page of the iSEE() function produces an iSEE app that showcases all eight core panel types. For simplicity, Figure 2.2 displays only the main component of each of those eight core panel types, for an example data set. Additional components accompanying each panel and the purpose of each panel will be discussed in a separate chapter.\n\n\n\n\n\n\n\n(a) Reduced dimension plot\n\n\n\n\n\n\n\n(b) Row data table\n\n\n\n\n\n\n\n(c) Feature assay plot\n\n\n\n\n\n\n\n\n\n(d) Column data plot\n\n\n\n\n\n\n\n(e) Row data plot\n\n\n\n\n\n\n\n(f) Sample assay plot\n\n\n\n\n\n\n\n\n\n(g) Column data table\n\n\n\n\n\n\n\n(h) Complex heatmap plot\n\n\n\n\nFigure 2.2: Main component the eight core panel type in the iSEE package, in their default configuration." }, { "objectID": "ui.html#actions", "href": "ui.html#actions", "title": "2  The user interface", "section": "2.3 Actions", - "text": "2.3 Actions\nOnce the panels are loaded into the interface, users are free to interact with the interface in any way they see fit.\n\n2.3.1 Scrolling\nUse the mouse wheel, trackpad, or directional arrows (up and down), to scroll up and down the interface, to bring panels into view.\nHorizontal scrolling is not possible in Shiny apps.\n\n\n\nFigure 2.3: Scrolling up and down the app interface.\n\n\nThere is no limit to the number of panels that may be added to the iSEE user interface.\nMeanwhile, no more than twelve panels may be displayed on a single row – one panel per unit in the 12-unit layout of pages produced by the shiny package – with rows being filled from left to right and panels exceeding the 12-unit layout being naturally pushed to new rows.\n\n\n2.3.2 Collabsible boxes\nClick on the header of collapsible boxes located under the panel output, to reveal interactive elements controlling various aspects of the contents displayed in each panel.\n\n\n\nFigure 2.4: Expanding collapsible boxes.\n\n\n\n\n2.3.3 Selection inputs\nClick on dropdown elements to reveal their choices. Click a different choice to see the panel output change accordingly.\n\n\n\nFigure 2.5: Changing the selected choice in dropdown menus.\n\n\n\n\n2.3.4 Checkboxes\nClick on checkboxes to toggle any number of mutually-compatible parameters.\n\n\n\nFigure 2.6: Toggling checkboxes." + "text": "2.3 Actions\nOnce the panels are loaded into the interface, users are free to interact with the interface in any way they see fit.\n\n2.3.1 Scrolling\nUse the mouse wheel, trackpad, or directional arrows (up and down), to scroll up and down the interface, to bring panels into view.\nHorizontal scrolling is not possible in Shiny apps.\n\n\n\nFigure 2.3: Scrolling up and down the app interface.\n\n\nThere is no limit to the number of panels that may be added to the iSEE user interface.\nMeanwhile, no more than twelve panels may be displayed on a single row – one panel per unit in the 12-unit layout of pages produced by the shiny package – with rows being filled from left to right and panels exceeding the 12-unit layout being placed on new rows.\n\n\n2.3.2 Collabsible boxes\nClick on the header of collapsible boxes located under the panel output, to reveal interactive elements controlling various aspects of the contents displayed in each panel.\n\n\n\nFigure 2.4: Expanding collapsible boxes.\n\n\n\n\n2.3.3 Selection inputs\nClick on dropdown elements to reveal their choices. Click a different choice to see the panel output change accordingly.\n\n\n\nFigure 2.5: Changing the selected choice in dropdown menus.\n\n\n\n\n2.3.4 Checkboxes\nClick on checkboxes to toggle any number of mutually-compatible parameters.\n\n\n\nFigure 2.6: Toggling checkboxes." }, { "objectID": "ui.html#collapsible-boxes-of-parameters", "href": "ui.html#collapsible-boxes-of-parameters", "title": "2  The user interface", "section": "2.4 Collapsible boxes of parameters", - "text": "2.4 Collapsible boxes of parameters\n\n2.4.1 Data parameters\nThe Data parameters collapsible box contains interactive elements that control the nature of the observations displayed in each panel.\nFor plots, that is typically the choice of variables shown along each axis.\nFor tables, that is typically the subset of columns hidden in the panel.\n\n\n\nFigure 2.7: The Data parameters box of the Reduced dimension plot panel, expanded to reveal its contents.\n\n\n\n\n2.4.2 Visual parameters\nThe Visual parameters collapsible box contains interactive elements that control the appearance of data points and non-data elements of panels that produce a plot.\nThat is typically, the color, shape, size, and opacity of data points. It may also include the possibility of faceting the plot by discrete variables along each axis, and further customisation of non-data elements of the plot such as axis labels and the plot legend.\n\n\n\nFigure 2.8: The Visual parameters box of the Reduced dimension plot panel, expanded and configured to reveal the ‘Color’, ‘Shape’, ‘Size’, and ‘Facet’ sections of its contents." + "text": "2.4 Collapsible boxes of parameters\n\n2.4.1 Data parameters\nThe Data parameters collapsible box contains interactive elements that control the nature of the observations displayed in each panel.\nFor plots, that is typically the choice of variables shown along each axis.\nFor tables, that is typically the subset of columns hidden in the panel.\n\n\n\nFigure 2.7: The Data parameters box of the Reduced dimension plot panel, expanded to reveal its contents.\n\n\n\n\n2.4.2 Visual parameters\nThe Visual parameters collapsible box contains interactive elements that control the appearance of data points and non-data elements of panels that produce a plot.\nThat is typically the color, shape, size, and opacity of data points. It may also include the possibility of faceting the plot by discrete variables along each axis, and further customisation of non-data elements of the plot such as axis labels and the plot legend.\n\n\n\nFigure 2.8: The Visual parameters box of the Reduced dimension plot panel, expanded and configured to reveal the ‘Color’, ‘Shape’, ‘Size’, and ‘Facet’ sections of its contents." }, { "objectID": "references.html", diff --git a/ui.html b/ui.html index 53b4088..dfa9f11 100644 --- a/ui.html +++ b/ui.html @@ -172,27 +172,27 @@

2 

2.1 Overview

-

In this chapter, we describe the contents and layout of a standard iSEE app.

+

In this chapter, we describe the contents and layout of a standard iSEE app.

Specifically, we focus on the appearance of the interactive point-and-click interface presented to end-users who come to simply explore the data set without any programming knowledge required.

-

Illustrative screenshots are taken from the iSEE app produced by the example code given in the help page of the iSEE() function, which can be access from an R console by typing either help(iSEE) or ?iSEE.

+

Illustrative screenshots are taken from the iSEE app produced by the example code given in the help page of the iSEE() function, which can be access from an R console by typing either help(iSEE) or ?iSEE.

2.2 Panels

-

Under entirely default settings, data sets loaded into the iSEE app are automatically parsed for standard information stored in SummarizedExperiment objects. Based on the information available and a set of eight core panel types designed to display different pieces of information, the iSEE() function automatically populates the interface with one panel of each type for which the relevant information is available.

+

Under entirely default settings, data sets loaded into the iSEE app are automatically parsed for standard information stored in SummarizedExperiment objects. Based on the information available and a set of eight core panel types designed to display different pieces of information, the iSEE() function automatically populates the interface with one panel of each type for which the relevant information is available.

Figure 2.1: First row of panel in the iSEE app interface, for an example data set.
-

The example code given in the help page of the iSEE() function produces an iSEE app that showcases all eight core panel types:

-
+

The example code given in the help page of the iSEE() function produces an iSEE app that showcases all eight core panel types. For simplicity, Figure 2.2 displays only the main component of each of those eight core panel types, for an example data set. Additional components accompanying each panel and the purpose of each panel will be discussed in a separate chapter.

+
-

+

(a) Reduced dimension plot
@@ -200,7 +200,7 @@

-

+

(b) Row data table
@@ -208,7 +208,7 @@

-

+

(c) Feature assay plot
@@ -218,7 +218,7 @@

-

+

(d) Column data plot
@@ -226,7 +226,7 @@

-

+

(e) Row data plot
@@ -234,7 +234,7 @@

-

+

(f) Sample assay plot
@@ -244,7 +244,7 @@

-

+

(g) Column data table
@@ -252,16 +252,15 @@

-

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(h) Complex heatmap plot

-

Figure 2.2: Core panel types in the iSEE package, in their default configuration.

+

Figure 2.2: Main component the eight core panel type in the iSEE package, in their default configuration.

-

Each core panel type is designed to display a different piece of information stored in the object. The purpose of each panel will be discussed in a separate chapter.

2.3 Actions

@@ -269,15 +268,15 @@

2.3.1 Scrolling

Use the mouse wheel, trackpad, or directional arrows (up and down), to scroll up and down the interface, to bring panels into view.

-

Horizontal scrolling is not possible in Shiny apps.

+

Horizontal scrolling is not possible in Shiny apps.

Figure 2.3: Scrolling up and down the app interface.
-

There is no limit to the number of panels that may be added to the iSEE user interface.

-

Meanwhile, no more than twelve panels may be displayed on a single row – one panel per unit in the 12-unit layout of pages produced by the shiny package – with rows being filled from left to right and panels exceeding the 12-unit layout being naturally pushed to new rows.

+

There is no limit to the number of panels that may be added to the iSEE user interface.

+

Meanwhile, no more than twelve panels may be displayed on a single row – one panel per unit in the 12-unit layout of pages produced by the shiny package – with rows being filled from left to right and panels exceeding the 12-unit layout being placed on new rows.

2.3.2 Collabsible boxes

@@ -327,7 +326,7 @@

2.4.2 Visual parameters

The Visual parameters collapsible box contains interactive elements that control the appearance of data points and non-data elements of panels that produce a plot.

-

That is typically, the color, shape, size, and opacity of data points. It may also include the possibility of faceting the plot by discrete variables along each axis, and further customisation of non-data elements of the plot such as axis labels and the plot legend.

+

That is typically the color, shape, size, and opacity of data points. It may also include the possibility of faceting the plot by discrete variables along each axis, and further customisation of non-data elements of the plot such as axis labels and the plot legend.