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# scMonitor | |||
scMonitor is a shinny application writen in R that allows to easily explore already processed scRNAseq seurat objects. | |||
Here, there is a video showing its features: | |||
<video width="720" height="420" controls> | |||
<source src="scMonitor.webm" type="video/webm"> | |||
<track src="scMonitor.eng.vtt" kind="subtitles" srclang="en" label="English" default> | |||
<track src="scMonitor.es.vtt" kind="subtitles" srclang="es" label="Spanish"> | |||
</video> |
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WEBVTT | |||
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In this video, I will present you | |||
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the shinny application scMonitor, which is | |||
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oriented to easily explore | |||
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a previously processed seurat object. | |||
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Firstly, you should select the file | |||
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containing the seurat object. | |||
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For now, the file format must be RDS. | |||
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Depending on the object size and | |||
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computer potency the loading | |||
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will take more or less time. | |||
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UMAP distribution that generates | |||
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is the same that shows as default, | |||
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usually clusters identified by seurat itself. | |||
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We can group colors by any | |||
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other variable that we have included in the | |||
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metadata from the object specifying it in "GroupBy". | |||
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Tipically, the sample origin or | |||
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a manual annotation | |||
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from the cell type. | |||
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Distribution can also be divided by | |||
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another variable selecting in "FacetBy". | |||
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In this case, we are looking at | |||
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the distribution of cell type | |||
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by the sample origin. | |||
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Another available visualization is to show expression | |||
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for a group of genes separated by a white space | |||
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over UMAP distribution. | |||
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With the "Height" bar we can adjust | |||
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the size in order to feel comfortable. | |||
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Finally, we can create signatures in order to visualize | |||
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their score from cells. | |||
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One must indicate the signature name and | |||
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on the box below specify the genes | |||
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that are included. Once added, you can | |||
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specify its name in the | |||
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signatures box. |
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WEBVTT | |||
00:00.700 --> 00:02.600 | |||
En este vídeo os voy a presentar | |||
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la aplicación "shinny" scMonitor, que está | |||
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orientada a explorar de forma sencilla un | |||
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objeto seurat previamente procesado. | |||
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Lo primero es seleccionar el fichero que | |||
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contiene ese objeto seurat. Por ahora, | |||
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el formato del fichero debe RDS. | |||
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En función del tamaño del objeto y | |||
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de la potencia del ordenador la carga | |||
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tardará más o menos. | |||
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La distribución UMAP que se genera | |||
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es la que se muestra por defecto, | |||
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normalmente los "clusters" identificados por el propio seurat. | |||
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Podemos agrupar los colores por cualquier | |||
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otra variable que hayamos incluido en los | |||
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metadatos del objeto especificándolo en "GroupBy". | |||
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Típicamente, el origen de la muestra o | |||
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una anotación | |||
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manual de tipo celular. | |||
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También se puede dividir la distribución en | |||
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función de una variable seleccionándolo en "FacetBy". | |||
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En este caso estamos viendo la | |||
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distribución de los tipos celulares en función | |||
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del origen de la muestra. | |||
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Otra visualización disponible es mostrar la expresión | |||
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de conjuntos de genes separados por un | |||
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espacio sobre la distribución UMAP. | |||
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Con la barra de altura podemos ajustar | |||
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el tamaño para que nos sea cómodo. | |||
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Finalmente, podemos crear signaturas para luego visualizar | |||
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el "score" de las células. | |||
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Hay que indicar el nombre de la signatura y | |||
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en la casilla inferior especificar los genes | |||
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que incluye. Una vez añadida se puede | |||
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especificar su nombre en la casilla de | |||
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signaturas. |