{"id":995,"date":"2022-03-01T10:42:59","date_gmt":"2022-03-01T10:42:22","guid":{"rendered":"https:\/\/www.ebi.ac.uk\/training\/materials\/single-cell-rna-seq-analysis-using-galaxy\/?page_id=995"},"modified":"2023-03-31T16:03:04","modified_gmt":"2023-03-31T16:03:04","slug":"practical-bulk-deconvolution","status":"publish","type":"page","link":"https:\/\/www.ebi.ac.uk\/training\/materials\/single-cell-rna-seq-analysis-using-galaxy-materials\/day-4\/practical-bulk-deconvolution\/","title":{"rendered":"Bulk deconvolution | Practical"},"content":{"rendered":"\n<p class=\"wp-block-paragraph\"><strong>Trainer: Mehmet Tekman<\/strong>, <meta charset=\"utf-8\">Wendi Bacon, Marisa Loach, Julia Jakiela, Graeme Tyson<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Overview:<\/strong> Bulk&nbsp;RNA-seq data contains a mixture of transcript signatures from several types of cells. We wish to deconvolve this mixture to obtain estimates of the proportions of cell types within the bulk sample. To do this, we can use&nbsp;single cell&nbsp;RNA-seq data as a reference for estimating the cell type proportions within the bulk data.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">In this tutorial, we will use bulk and&nbsp;single-cell&nbsp;RNA-seq data, including matrices of similar tissues from different sources, to illustrate how to infer cell type abundances from bulk&nbsp;RNA-seq.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Materials:<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">For Galaxy tutorials use Chrome, Safari or Firefox as your browser, not Internet Explorer!<\/p>\n\n\n\n<ul class=\"wp-block-list\"><li><a href=\"https:\/\/training.galaxyproject.org\/training-material\/topics\/single-cell\/tutorials\/bulk-music\/tutorial.html\">Practical instructions <\/a><\/li><li><a href=\"https:\/\/humancellatlas.usegalaxy.eu\/u\/mehmet-tekman\/h\/deconvolution-cell-type-inference-of-human-pancreas-data-input-data\">Practical input 1<\/a><\/li><li><a href=\"https:\/\/humancellatlas.usegalaxy.eu\/u\/mehmet-tekman\/h\/deconvolution-dendrogram-of-mouse-data-input-data\" data-type=\"URL\" data-id=\"https:\/\/humancellatlas.usegalaxy.eu\/u\/mehmet-tekman\/h\/deconvolution-dendrogram-of-mouse-data-input-data\">Practical input 2<\/a><\/li><li><a href=\"https:\/\/humancellatlas.usegalaxy.eu\/u\/mehmet-tekman\/h\/deconvolution-cell-type-inference-of-human-pancreas-data\">Practical answer key 1<\/a><\/li><li><a href=\"https:\/\/humancellatlas.usegalaxy.eu\/u\/mehmet-tekman\/h\/deconvolution-dendrogram-of-mouse-data\">Practical answer key 2<\/a><\/li><li><a href=\"https:\/\/gallantries.github.io\/video-library\/videos\/single-cell\/bulk-music\/tutorial\/\">Practical screencast<\/a><\/li><\/ul>\n\n\n\n<p class=\"wp-block-paragraph\"><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Trainer: Mehmet Tekman, Wendi Bacon, Marisa Loach, Julia Jakiela, Graeme Tyson Overview: Bulk&nbsp;RNA-seq data contains a mixture of transcript signatures from several types of cells. We wish to deconvolve this mixture to obtain estimates of the proportions of cell types within the bulk sample. To do this, we can use&nbsp;single cell&nbsp;RNA-seq data as a reference&#8230;<\/p>\n","protected":false},"author":34,"featured_media":0,"parent":15,"menu_order":4,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-995","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/www.ebi.ac.uk\/training\/materials\/single-cell-rna-seq-analysis-using-galaxy-materials\/wp-json\/wp\/v2\/pages\/995","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.ebi.ac.uk\/training\/materials\/single-cell-rna-seq-analysis-using-galaxy-materials\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.ebi.ac.uk\/training\/materials\/single-cell-rna-seq-analysis-using-galaxy-materials\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.ebi.ac.uk\/training\/materials\/single-cell-rna-seq-analysis-using-galaxy-materials\/wp-json\/wp\/v2\/users\/34"}],"replies":[{"embeddable":true,"href":"https:\/\/www.ebi.ac.uk\/training\/materials\/single-cell-rna-seq-analysis-using-galaxy-materials\/wp-json\/wp\/v2\/comments?post=995"}],"version-history":[{"count":15,"href":"https:\/\/www.ebi.ac.uk\/training\/materials\/single-cell-rna-seq-analysis-using-galaxy-materials\/wp-json\/wp\/v2\/pages\/995\/revisions"}],"predecessor-version":[{"id":1829,"href":"https:\/\/www.ebi.ac.uk\/training\/materials\/single-cell-rna-seq-analysis-using-galaxy-materials\/wp-json\/wp\/v2\/pages\/995\/revisions\/1829"}],"up":[{"embeddable":true,"href":"https:\/\/www.ebi.ac.uk\/training\/materials\/single-cell-rna-seq-analysis-using-galaxy-materials\/wp-json\/wp\/v2\/pages\/15"}],"wp:attachment":[{"href":"https:\/\/www.ebi.ac.uk\/training\/materials\/single-cell-rna-seq-analysis-using-galaxy-materials\/wp-json\/wp\/v2\/media?parent=995"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}