docs: dropped express link

selkamand · Aug 5, 2024 · 53fb638 · 53fb638
1 parent fe77384
commit 53fb638
Show file tree

Hide file tree

Showing 4 changed files with 2 additions and 5 deletions.
diff --git a/paper/jats/paper.jats b/paper/jats/paper.jats
@@ -145,10 +145,7 @@ a Creative Commons Attribution 4.0 International License (CC BY
     selected in the t-SNE are enriched for triple negative breast
     cancers. In contrast to the oncoplot, the methylation UMAP shows no
     strong clustering, consistent with knowledge of methylation patterns
-    in triple negative breast cancer. Expression and methylation plots
-    were produced using the
-    <ext-link ext-link-type="uri" xlink:href="https://github.com/selkamand/express">express</ext-link>
-    package.
+    in triple negative breast cancer.
     <styled-content id="figU003Amultimodal_selection"></styled-content></p></caption>
     <graphic mimetype="image" mime-subtype="png" xlink:href="multimodal_selection_with_lasso.png" />
   </fig>

diff --git a/paper/paper.docx b/paper/paper.docx
diff --git a/paper/paper.md b/paper/paper.md
@@ -34,7 +34,7 @@ The ggoncoplot R package generates interactive oncoplots to visualize mutational
 ![ggoncoplot output visualising mutational trends in the TCGA breast carcinoma cohort. Individual patient samples are plotted on the x-axis, hierarchically sorted so that samples with the most frequent gene mutations appear on the leftmost side. The plot indicates that PIK3CA is the most frequently mutated gene, followed by TP53. Marginal plots indicate the total number of mutations per sample (top), and the number of samples showing mutations in each gene, coloured by mutation type (right). A range of clinical features, including progesterone and estrogen receptor status are shown on the marginal plot at the bottom. A detailed description of the ggoncoplot sorting algorithm is available [here](https://selkamand.github.io/ggoncoplot/articles/sorting_algorithm.html). \label{fig:oncoplot}](oncoplot.pdf)
 
 
-![Example of the ggoncoplot shown in Figure 1, where the oncoplot has been dynamically cross-linked to a gene expression t-SNE plot (top left) and a methylation UMAP (top right). Here, the lasso tool was used to select a cluster of gene expression data points (i.e., individual samples) in the t-SNE plot. Selected samples were automatically highlighted on the UMAP and oncoplot. This reveals that samples which cluster on the left of the t-SNE plot also cluster in the oncoplot, chiefly containing mutations in TP53 and wild type PIK3CA. The plots of progesterone, estrogen, HER2 status and triple negative classification show that the samples selected in the t-SNE are enriched for triple negative breast cancers.  In contrast to the oncoplot, the methylation UMAP shows no strong clustering, consistent with knowledge of methylation patterns in triple negative breast cancer. Expression and methylation plots were produced using the [express](https://github.com/selkamand/express) package. \label{fig:multimodal_selection}](multimodal_selection_with_lasso.png)
+![Example of the ggoncoplot shown in Figure 1, where the oncoplot has been dynamically cross-linked to a gene expression t-SNE plot (top left) and a methylation UMAP (top right). Here, the lasso tool was used to select a cluster of gene expression data points (i.e., individual samples) in the t-SNE plot. Selected samples were automatically highlighted on the UMAP and oncoplot. This reveals that samples which cluster on the left of the t-SNE plot also cluster in the oncoplot, chiefly containing mutations in TP53 and wild type PIK3CA. The plots of progesterone, estrogen, HER2 status and triple negative classification show that the samples selected in the t-SNE are enriched for triple negative breast cancers.  In contrast to the oncoplot, the methylation UMAP shows no strong clustering, consistent with knowledge of methylation patterns in triple negative breast cancer. \label{fig:multimodal_selection}](multimodal_selection_with_lasso.png)
 
 
 

diff --git a/paper/paper.pdf b/paper/paper.pdf
Original file line number	Diff line number	Diff line change
Expand Up		@@ -34,7 +34,7 @@ The ggoncoplot R package generates interactive oncoplots to visualize mutational
		![ggoncoplot output visualising mutational trends in the TCGA breast carcinoma cohort. Individual patient samples are plotted on the x-axis, hierarchically sorted so that samples with the most frequent gene mutations appear on the leftmost side. The plot indicates that PIK3CA is the most frequently mutated gene, followed by TP53. Marginal plots indicate the total number of mutations per sample (top), and the number of samples showing mutations in each gene, coloured by mutation type (right). A range of clinical features, including progesterone and estrogen receptor status are shown on the marginal plot at the bottom. A detailed description of the ggoncoplot sorting algorithm is available [here](https://selkamand.github.io/ggoncoplot/articles/sorting_algorithm.html). \label{fig:oncoplot}](oncoplot.pdf)


		![Example of the ggoncoplot shown in Figure 1, where the oncoplot has been dynamically cross-linked to a gene expression t-SNE plot (top left) and a methylation UMAP (top right). Here, the lasso tool was used to select a cluster of gene expression data points (i.e., individual samples) in the t-SNE plot. Selected samples were automatically highlighted on the UMAP and oncoplot. This reveals that samples which cluster on the left of the t-SNE plot also cluster in the oncoplot, chiefly containing mutations in TP53 and wild type PIK3CA. The plots of progesterone, estrogen, HER2 status and triple negative classification show that the samples selected in the t-SNE are enriched for triple negative breast cancers. In contrast to the oncoplot, the methylation UMAP shows no strong clustering, consistent with knowledge of methylation patterns in triple negative breast cancer. Expression and methylation plots were produced using the [express](https://github.com/selkamand/express) package. \label{fig:multimodal_selection}](multimodal_selection_with_lasso.png)
		![Example of the ggoncoplot shown in Figure 1, where the oncoplot has been dynamically cross-linked to a gene expression t-SNE plot (top left) and a methylation UMAP (top right). Here, the lasso tool was used to select a cluster of gene expression data points (i.e., individual samples) in the t-SNE plot. Selected samples were automatically highlighted on the UMAP and oncoplot. This reveals that samples which cluster on the left of the t-SNE plot also cluster in the oncoplot, chiefly containing mutations in TP53 and wild type PIK3CA. The plots of progesterone, estrogen, HER2 status and triple negative classification show that the samples selected in the t-SNE are enriched for triple negative breast cancers. In contrast to the oncoplot, the methylation UMAP shows no strong clustering, consistent with knowledge of methylation patterns in triple negative breast cancer. \label{fig:multimodal_selection}](multimodal_selection_with_lasso.png)



Expand Down