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content moved around a bit to avoid conflicts in panel&package combos
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@federicomarini
federicomarini committed May 5, 2024
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Expand Up @@ -49,18 +49,9 @@ We will use the following packages throughout its content (make sure to have the

```{r pkgs}
library("iSEE")
library("iSEEfier")
# library("iSEEu")
library("iSEEde")
library("iSEEpathways")
library("iSEEhub")
library("iSEEindex")
```



# iSEE a challenge: let's reproduce any figure!

We'd like to open up a challenge, with some simple rules:
Expand All @@ -71,6 +62,92 @@ We'd like to open up a challenge, with some simple rules:
Let's suggest a couple of figure/figure panels!
Enter a couple of suggestions in this GSheet: https://docs.google.com/spreadsheets/d/1poE713rXqzfNdPcKAPN2AxJYXhaxy8GwgAjRsk_UiK8/edit?usp=sharing

# iSEEde and iSEEpathways

iSEEde and iSEEpathways: ideal companions for exploring DE results

We first load the processed `macrophage` data (derived from the work of [@Alasoo2018]) - on this, we already ran the workflow of `DESeq2` [@Love2014] to identify the differentially expressed genes.

```{r}
macrophage_location <- system.file("datasets", "sce_macrophage_readytouse.RDS",
package = "iUSEiSEE"
)
macrophage_location
sce_macrophage <- readRDS(macrophage_location)
library("iSEE")
library("iSEEde")
library("iSEEpathways")
```

`r Biocpkg("iSEEde")` and `r Biocpkg("iSEEpathways")` are two new Bioconductor packages that provide `r Biocpkg("iSEE")` panels specifically aimed towards exploration of differential expression and pathway analysis results.
More precisely, `r Biocpkg("iSEEde")` provides the `VolcanoPlot`, `MAPlot`, `LogFCLogFCPlot` and `DETable` panels.
These panels can be configured to extract data that was added via the `embedContrastResults()` function above.
Let's look at an example:

```{r}
app <- iSEE(sce_macrophage, initial = list(
DETable(
ContrastName = "IFNgTRUE.SL1344TRUE.DESeq2",
HiddenColumns = c("baseMean", "lfcSE", "stat")
),
VolcanoPlot(ContrastName = "IFNgTRUE.SL1344TRUE.DESeq2"),
MAPlot(ContrastName = "IFNgTRUE.SL1344TRUE.DESeq2")
))
```

```{r, echo=FALSE}
SCREENSHOT("images/isee_de_setup1.png", delay = 20)
```


<!-- Possible actions: -->
<!-- select some genes from any panel and pass the selection to others -->
<!-- move panels around, add some, update configuration -->
<!-- hover with the mouse to have the tooltip show up -->
<!-- usual iSEE magic: export code for the plots -->

Note how it is easy to switch to a different contrast in any of the panels.

```{r}
app <- iSEE(sce_macrophage, initial = list(
iSEEde::DETable(
ContrastName = "IFNgTRUE.SL1344TRUE.DESeq2",
HiddenColumns = c("baseMean", "lfcSE", "stat")
),
iSEEde::VolcanoPlot(ContrastName = "IFNgTRUE.SL1344TRUE.DESeq2"),
iSEEde::MAPlot(ContrastName = "IFNgTRUE.SL1344TRUE.DESeq2"),
PathwaysTable(
ResultName = "IFNgTRUE.SL1344TRUE.limma.fgsea",
Selected = "GO:0046324"
),
ComplexHeatmapPlot(
RowSelectionSource = "PathwaysTable1",
CustomRows = FALSE, ColumnData = "condition_name",
ClusterRows = TRUE, Assay = "vst"
),
FgseaEnrichmentPlot(
ResultName = "IFNgTRUE.SL1344TRUE.limma.fgsea",
PathwayId = "GO:0046324"
)
))
```

```{r, echo=FALSE}
SCREENSHOT("images/isee_de_setup2.png", delay = 30)
```

<!-- Possible actions: -->
<!-- select a pathway from PAT1 -->
<!-- transform vst data in heatmap, center -->
<!-- receive row selection in volcano and MA plot -->
<!-- change coloring to "row selection" -->
<!-- select alternative contrast and see all dependencies updated -->
<!-- usual iSEE magic: export code for the plots -->
<!-- usual iSEE magic: export code for the panel configuration -->


# iSEEfier

Let's say we are interested in visualizing the expression of a list of specific marker genes in one view, or maybe we created different initial states separately, but would like to visualize them in the same instance. As we previously learned, we can do a lot of these tasks by running the command:
Expand All @@ -88,6 +165,8 @@ In this section, we will illustrate a simple example of how to use `r Biocpkg("i
We start by loading the data:

```{r}
library("iSEEfier")
# import data
sce <- readRDS(
file = system.file("datasets", "sce_pbmc3k.RDS", package = "iUSEiSEE")
Expand Down Expand Up @@ -217,6 +296,9 @@ The main functionality of this package is to define a custom landing page allowi
To see how to configure such an app, we will create a small example:

```{r}
library("iSEE")
library("iSEEindex")
bfc <- BiocFileCache(cache = tempdir())
dataset_fun <- function() {
Expand Down Expand Up @@ -251,90 +333,6 @@ Potential use cases can include:
* An app to mirror and enhance the content of e.g. the cellxgene data portal
* Got any ideas on how to use iSEE for such deployments?

# iSEEde and iSEEpathways

iSEEde and iSEEpathways: ideal companions for exploring DE results

We first load the processed `macrophage` data (derived from the work of [@Alasoo2018]) - on this, we already ran the workflow of `DESeq2` [@Love2014] to identify the differentially expressed genes.

```{r}
macrophage_location <- system.file("datasets", "sce_macrophage_readytouse.RDS",
package = "iUSEiSEE"
)
macrophage_location
sce_macrophage <- readRDS(macrophage_location)
library("iSEE")
library("iSEEde")
library("iSEEpathways")
```

`r Biocpkg("iSEEde")` and `r Biocpkg("iSEEpathways")` are two new Bioconductor packages that provide `r Biocpkg("iSEE")` panels specifically aimed towards exploration of differential expression and pathway analysis results.
More precisely, `r Biocpkg("iSEEde")` provides the `VolcanoPlot`, `MAPlot`, `LogFCLogFCPlot` and `DETable` panels.
These panels can be configured to extract data that was added via the `embedContrastResults()` function above.
Let's look at an example:

```{r}
app <- iSEE(sce_macrophage, initial = list(
DETable(
ContrastName = "IFNgTRUE.SL1344TRUE.DESeq2",
HiddenColumns = c("baseMean", "lfcSE", "stat")
),
VolcanoPlot(ContrastName = "IFNgTRUE.SL1344TRUE.DESeq2"),
MAPlot(ContrastName = "IFNgTRUE.SL1344TRUE.DESeq2")
))
```

```{r, echo=FALSE}
SCREENSHOT("images/isee_de_setup1.png", delay = 20)
```


<!-- Possible actions: -->
<!-- select some genes from any panel and pass the selection to others -->
<!-- move panels around, add some, update configuration -->
<!-- hover with the mouse to have the tooltip show up -->
<!-- usual iSEE magic: export code for the plots -->

Note how it is easy to switch to a different contrast in any of the panels.

```{r}
app <- iSEE(sce_macrophage, initial = list(
DETable(
ContrastName = "IFNgTRUE.SL1344TRUE.DESeq2",
HiddenColumns = c("baseMean", "lfcSE", "stat")
),
VolcanoPlot(ContrastName = "IFNgTRUE.SL1344TRUE.DESeq2"),
MAPlot(ContrastName = "IFNgTRUE.SL1344TRUE.DESeq2"),
PathwaysTable(
ResultName = "IFNgTRUE.SL1344TRUE.limma.fgsea",
Selected = "GO:0046324"
),
ComplexHeatmapPlot(
RowSelectionSource = "PathwaysTable1",
CustomRows = FALSE, ColumnData = "condition_name",
ClusterRows = TRUE, Assay = "vst"
),
FgseaEnrichmentPlot(
ResultName = "IFNgTRUE.SL1344TRUE.limma.fgsea",
PathwayId = "GO:0046324"
)
))
```

```{r, echo=FALSE}
SCREENSHOT("images/isee_de_setup2.png", delay = 30)
```

<!-- Possible actions: -->
<!-- select a pathway from PAT1 -->
<!-- transform vst data in heatmap, center -->
<!-- receive row selection in volcano and MA plot -->
<!-- change coloring to "row selection" -->
<!-- select alternative contrast and see all dependencies updated -->
<!-- usual iSEE magic: export code for the plots -->
<!-- usual iSEE magic: export code for the panel configuration -->

# Tours: help and storytelling

Expand Down

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