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<title>Importing Spatial Data</title> |
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left: 100%; |
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margin-top: -6px; |
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margin-left: -1px; |
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border-radius: 0 6px 6px 6px; |
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border-width: 5px 0 5px 5px; |
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margin-top: 5px; |
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// active menu anchor |
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min-height: 44px; |
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overflow-y: auto; |
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border: 1px solid #ddd; |
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border-radius: 4px; |
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padding: 10px; |
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border-right: 1px solid #ddd; |
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} |
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content: "\e258"; |
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font-family: 'Glyphicons Halflings'; |
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display: block; |
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display: block; |
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float: none; |
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display: none; |
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</style> |
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#TOC { |
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margin: 25px 0px 20px 0px; |
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} |
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@media (max-width: 768px) { |
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#TOC { |
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position: relative; |
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width: 100%; |
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} |
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@media print { |
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/* see https://github.com/w3c/csswg-drafts/issues/4434 */ |
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float: right; |
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} |
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} |
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.toc-content { |
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padding-left: 30px; |
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padding-right: 40px; |
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} |
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div.main-container { |
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max-width: 1200px; |
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} |
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div.tocify { |
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width: 20%; |
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max-width: 260px; |
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max-height: 85%; |
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} |
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@media (min-width: 768px) and (max-width: 991px) { |
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div.tocify { |
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width: 25%; |
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} |
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} |
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@media (max-width: 767px) { |
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div.tocify { |
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width: 100%; |
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max-width: none; |
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} |
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} |
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.tocify ul, .tocify li { |
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line-height: 20px; |
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} |
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font-size: 0.90em; |
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border-radius: 0px; |
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} |
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.tocify-subheader { |
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display: inline; |
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} |
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.tocify-subheader .tocify-item { |
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font-size: 0.95em; |
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} |
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</style> |
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</head> |
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<body> |
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<div class="container-fluid main-container"> |
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<!-- setup 3col/9col grid for toc_float and main content --> |
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<div class="row"> |
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<div class="col-xs-12 col-sm-4 col-md-3"> |
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<div id="TOC" class="tocify"> |
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</div> |
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</div> |
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<div class="toc-content col-xs-12 col-sm-8 col-md-9"> |
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<div class="navbar navbar-default navbar-fixed-top" role="navigation"> |
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<div class="container"> |
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<div class="navbar-header"> |
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<button type="button" class="navbar-toggle collapsed" data-toggle="collapse" data-bs-toggle="collapse" data-target="#navbar" data-bs-target="#navbar"> |
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<span class="icon-bar"></span> |
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<span class="icon-bar"></span> |
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<span class="icon-bar"></span> |
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</button> |
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<a class="navbar-brand" href="index.html">VoltRon</a> |
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</div> |
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<div id="navbar" class="navbar-collapse collapse"> |
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<ul class="nav navbar-nav"> |
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<li> |
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<a href="tutorials.html">Explore</a> |
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</li> |
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<li class="dropdown"> |
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<a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" data-bs-toggle="dropdown" aria-expanded="false"> |
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Vignette |
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<span class="caret"></span> |
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</a> |
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<ul class="dropdown-menu" role="menu"> |
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<li class="dropdown-submenu"> |
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<a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" data-bs-toggle="dropdown" aria-expanded="false">Spatial Data Integration</a> |
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<ul class="dropdown-menu" role="menu"> |
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<li> |
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<a href="registration.html">Spatial Data Alignment</a> |
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</li> |
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<li> |
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<a href="multiomic.html">Multi-omic Integration</a> |
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</li> |
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<li> |
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<a href="nicheclustering.html">Niche Clustering</a> |
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</li> |
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</ul> |
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</li> |
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<li class="dropdown-submenu"> |
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<a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" data-bs-toggle="dropdown" aria-expanded="false">Downstream Analysis</a> |
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<ul class="dropdown-menu" role="menu"> |
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<li> |
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<a href="roianalysis.html">ROI Analysis</a> |
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</li> |
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<li> |
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<a href="spotanalysis.html">Cell/Spot Analysis</a> |
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</li> |
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<li> |
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<a href="moleculeanalysis.html">Molecule Analysis</a> |
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</li> |
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<li> |
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<a href="pixelanalysis.html">Pixels (Image Only) Analysis</a> |
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</li> |
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</ul> |
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</li> |
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<li class="dropdown-submenu"> |
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<a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" data-bs-toggle="dropdown" aria-expanded="false">Utilities</a> |
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<ul class="dropdown-menu" role="menu"> |
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<li> |
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<a href="interactive.html">Interactive Utilities</a> |
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</li> |
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<li> |
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<a href="importingdata.html">Importing Spatial Data</a> |
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</li> |
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<li> |
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<a href="voltronobjects.html">Working with VoltRon Objects</a> |
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</li> |
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<li> |
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<a href="conversion.html">Converting VoltRon Objects</a> |
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</li> |
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<li> |
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<a href="ondisk.html">OnDisk-based Analysis Utilities</a> |
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</li> |
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</ul> |
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</li> |
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</ul> |
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</li> |
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</ul> |
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<ul class="nav navbar-nav navbar-right"> |
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<li class="dropdown"> |
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<a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" data-bs-toggle="dropdown" aria-expanded="false"> |
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<span class="fa fa-envelope-o"></span> |
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Contact |
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<span class="caret"></span> |
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</a> |
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<ul class="dropdown-menu" role="menu"> |
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<li> |
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<a href="https://bioinformatics.mdc-berlin.de">Altuna Lab/BIMSB Bioinfo</a> |
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</li> |
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<li> |
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<a href="https://www.mdc-berlin.de/landthaler">Landthaler Lab/BIMSB</a> |
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</li> |
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</ul> |
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</li> |
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<li class="dropdown"> |
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<a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" data-bs-toggle="dropdown" aria-expanded="false"> |
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<span class="fa fa-github"></span> |
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GitHub |
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<span class="caret"></span> |
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</a> |
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<ul class="dropdown-menu" role="menu"> |
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<li> |
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<a href="https://github.com/BIMSBbioinfo/VoltRon">VoltRon</a> |
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</li> |
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<li> |
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<a href="https://github.com/BIMSBbioinfo">BIMSB Bioinfo</a> |
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</li> |
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</ul> |
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</li> |
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</ul> |
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</div><!--/.nav-collapse --> |
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</div><!--/.container --> |
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</div><!--/.navbar --> |
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<div id="header"> |
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<h1 class="title toc-ignore">Importing Spatial Data</h1> |
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</div> |
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<style> |
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.title{ |
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display: none; |
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} |
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body { |
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text-align: justify |
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} |
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.center { |
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display: block; |
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margin-left: auto; |
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margin-right: auto; |
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} |
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table, th, td { |
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border-collapse: collapse; |
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align-self: center; |
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padding-right: 10px; |
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padding-left: 10px; |
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} |
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</style> |
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<style type="text/css"> |
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.watch-out { |
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color: black; |
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} |
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</style> |
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<p><br></p> |
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<div id="working-with-voltron-objects" class="section level1"> |
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<h1>Working with VoltRon objects</h1> |
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<p>In this tutorial, we will cover some of the fundemantel built-in |
|
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functions of VoltRon to manage data, images and spatial information of |
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assays. Here is the list of example datasets included in the |
|
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Package.</p> |
|
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<pre class="r watch-out"><code>data("visium_data") |
|
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data("melc_data") |
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data("xenium_data") |
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data("merged_object")</code></pre> |
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<p><br></p> |
|
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<div id="samplemetadata" class="section level2"> |
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<h2>Sample Metadata</h2> |
|
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<p>The sample metadata is a summarized data frame which provides |
|
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informations on assays, layers and sample (tissue blocks) included in |
|
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the VoltRon object. You can use the <strong>SampleMetadata</strong> |
|
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function to call this table. The row names are the unique assay IDs, |
|
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following assay types (e.g. Visium), layer name and Sample (typicall |
|
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tissue block with multiple layers and assays).</p> |
|
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<pre class="r watch-out"><code>SampleMetadata(visium_data)</code></pre> |
|
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<pre><code>## Assay Layer Sample |
|
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## Assay1 Visium Section1 Anterior1</code></pre> |
|
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<p><br></p> |
|
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</div> |
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<div id="metadata" class="section level2"> |
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<h2>Metadata</h2> |
|
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<p>The <strong>Metadata</strong> function calls the metadata table of |
|
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the main assay type (see <a href="#assays">vrMainAssay</a>).</p> |
|
|
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<pre class="r watch-out"><code>Metadata(visium_data)</code></pre> |
|
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<pre><code>## id Count assay_id Assay Layer Sample |
|
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## AAAGGCTCTCGCGCCG-1_Assay1 AAAGGCTCTCGCGCCG-1_Assay1 39690 Assay1 Visium Section1 Anterior1 |
|
|
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## AAATGGCCCGTGCCCT-1_Assay1 AAATGGCCCGTGCCCT-1_Assay1 33516 Assay1 Visium Section1 Anterior1 |
|
|
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## AAATTACACGACTCTG-1_Assay1 AAATTACACGACTCTG-1_Assay1 12250 Assay1 Visium Section1 Anterior1 |
|
|
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## AAGACATACGTGGTTT-1_Assay1 AAGACATACGTGGTTT-1_Assay1 31821 Assay1 Visium Section1 Anterior1 |
|
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## ACCTACTATAAATCTA-1_Assay1 ACCTACTATAAATCTA-1_Assay1 41387 Assay1 Visium Section1 Anterior1 |
|
|
502 |
## ACGCGGGCCAAGGACA-1_Assay1 ACGCGGGCCAAGGACA-1_Assay1 48003 Assay1 Visium Section1 Anterior1</code></pre> |
|
|
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<p>You can also specify the assay ID or the assay type to call metadata |
|
|
504 |
of a subset of spatial points.</p> |
|
|
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<pre class="r watch-out"><code>Metadata(visium_data, assay = "Visium") |
|
|
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Metadata(visium_data, assay = "Assay1")</code></pre> |
|
|
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<p>The <strong>type</strong> argument returns all spatial points of a |
|
|
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given spatial point type (ROI, spot, cell, molecule or tile).</p> |
|
|
509 |
<pre class="r watch-out"><code>Metadata(visium_data, type = "spot")</code></pre> |
|
|
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<p>If the type argument is specified as <strong>all</strong>. Then this |
|
|
511 |
would return the VoltRon Metadata Object (vrMetadata)</p> |
|
|
512 |
<pre class="r watch-out"><code>Metadata(visium_data, type = "all")</code></pre> |
|
|
513 |
<pre><code>## VoltRon Metadata Object |
|
|
514 |
## This object includes: |
|
|
515 |
## 100 spots</code></pre> |
|
|
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<p><br></p> |
|
|
517 |
</div> |
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|
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<div id="spatialpoints" class="section level2"> |
|
|
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<h2>Spatial Points</h2> |
|
|
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<p>In a VoltRon object, spatial points are spatially defined entities |
|
|
521 |
with coordinates, segments which are of any of five assay types (ROI, |
|
|
522 |
spot, cell, molecule and tile).</p> |
|
|
523 |
<p>The <strong>vrSpatialPoints</strong> function return the IDs of these |
|
|
524 |
entities for further downstream operations, such as subsetting etc.</p> |
|
|
525 |
<pre class="r watch-out"><code>vrSpatialPoints(visium_data)</code></pre> |
|
|
526 |
<pre><code>## [1] "AAAGGCTCTCGCGCCG-1_Assay1" "AAATGGCCCGTGCCCT-1_Assay1" "AAATTACACGACTCTG-1_Assay1"</code></pre> |
|
|
527 |
<p>You can also specify the assay ID or the assay type to call metadata |
|
|
528 |
of a subset of spatial points.</p> |
|
|
529 |
<pre class="r watch-out"><code>vrSpatialPoints(visium_data, assay = "Visium") |
|
|
530 |
vrSpatialPoints(visium_data, assay = "Assay1")</code></pre> |
|
|
531 |
<pre><code>## [1] "AAAGGCTCTCGCGCCG-1_Assay1" "AAATGGCCCGTGCCCT-1_Assay1" "AAATTACACGACTCTG-1_Assay1"</code></pre> |
|
|
532 |
<p><br></p> |
|
|
533 |
</div> |
|
|
534 |
<div id="assays" class="section level2"> |
|
|
535 |
<h2>Assays</h2> |
|
|
536 |
<p>The default (or main) assay of the VoltRon object is typically shown |
|
|
537 |
when printed (next to the assay name says “main” in paranthesis)</p> |
|
|
538 |
<pre class="r watch-out"><code>melc_data</code></pre> |
|
|
539 |
<pre><code>## VoltRon Object |
|
|
540 |
## control_case_3: |
|
|
541 |
## Layers: Section1 |
|
|
542 |
## Assays: MELC(Main) |
|
|
543 |
## Features: main(Main)</code></pre> |
|
|
544 |
<p>You can also call/get the name of the default (or main) using the |
|
|
545 |
<strong>vrMainAssay</strong> function</p> |
|
|
546 |
<pre class="r watch-out"><code>vrMainAssay(melc_data)</code></pre> |
|
|
547 |
<pre><code>## [1] "MELC"</code></pre> |
|
|
548 |
<p>You can also set the main assay yourself, but only the assay types |
|
|
549 |
given in the <strong>Assay</strong> column of |
|
|
550 |
<strong>SampleMetadata(object)</strong>.</p> |
|
|
551 |
<pre class="r watch-out"><code>SampleMetadata(melc_data)</code></pre> |
|
|
552 |
<pre><code>## Assay Layer Sample |
|
|
553 |
## Assay1 MELC Section1 control_case_3</code></pre> |
|
|
554 |
<pre class="r watch-out"><code>vrMainAssay(melc_data) <- "MELC"</code></pre> |
|
|
555 |
<p>You can also get the assay IDs associated with the main assay using |
|
|
556 |
<strong>vrAssayNames</strong> function.</p> |
|
|
557 |
<pre class="r watch-out"><code>vrAssayNames(melc_data)</code></pre> |
|
|
558 |
<pre><code>## [1] "Assay1"</code></pre> |
|
|
559 |
<p>The assay type can be provided with the <strong>assay</strong> |
|
|
560 |
arguement to get type specific assay IDs</p> |
|
|
561 |
<pre class="r watch-out"><code>vrAssayNames(melc_data, assay = "MELC")</code></pre> |
|
|
562 |
<pre><code>## [1] "Assay1"</code></pre> |
|
|
563 |
<p><br></p> |
|
|
564 |
</div> |
|
|
565 |
<div id="coordinates-and-segments" class="section level2"> |
|
|
566 |
<h2>Coordinates and Segments</h2> |
|
|
567 |
<p>The <strong>vrCoordinates</strong> function is used to call the |
|
|
568 |
centroids of spots, cells and all other spatial points types with |
|
|
569 |
VoltRon objects.</p> |
|
|
570 |
<pre class="r watch-out"><code>vrCoordinates(visium_data)</code></pre> |
|
|
571 |
<pre><code>## x y z |
|
|
572 |
## CCTTGACCACTTTATT-1_Assay1 463.78658 183.1497 0 |
|
|
573 |
## ATTTGTCTTGGGAGCT-1_Assay1 374.97419 275.8864 0 |
|
|
574 |
## TCACGCATTGTAGATC-1_Assay1 250.58520 319.1566 0 |
|
|
575 |
## CCGAGCTGTGCTTGTC-1_Assay1 474.47505 411.9449 0 |
|
|
576 |
## GCATGGGTACTGACGC-1_Assay1 87.10844 269.6902 0 |
|
|
577 |
## AGTCGGCCCAAACGAC-1_Assay1 215.00861 368.6231 0</code></pre> |
|
|
578 |
<p>You can also specify the assay ID or the assay type to call |
|
|
579 |
coordinates of a subset of spatial points.</p> |
|
|
580 |
<pre class="r watch-out"><code>vrCoordinates(visium_data, assay = "Visium") |
|
|
581 |
vrCoordinates(visium_data, assay = "Assay1")</code></pre> |
|
|
582 |
<p><br></p> |
|
|
583 |
<p>Each assay a VoltRon object may incorporate indefinite number of |
|
|
584 |
coordinate systems. One can look for these coordinate systems using the |
|
|
585 |
<strong>vrMainSpatial</strong> function, and select one of systems to |
|
|
586 |
call coordinates (see <a href="#image">vrMainSpatial</a>)</p> |
|
|
587 |
<pre class="r watch-out"><code>vrCoordinates(visium_data, spatial_name = "main")</code></pre> |
|
|
588 |
<p>The <strong>reg</strong> option in the <strong>vrCoordinates</strong> |
|
|
589 |
function looks for a registered version of the main coordinate system |
|
|
590 |
and returns its coordinates (if there is any).</p> |
|
|
591 |
<pre class="r watch-out"><code>vrCoordinates(visium_data, spatial_name = "main", reg = TRUE)</code></pre> |
|
|
592 |
<pre><code>## Warning in .local(object, ...): There are no registered spatial systems with name main!</code></pre> |
|
|
593 |
<pre><code>## x y z |
|
|
594 |
## CCTTGACCACTTTATT-1_Assay1 463.78658 183.1497 0 |
|
|
595 |
## ATTTGTCTTGGGAGCT-1_Assay1 374.97419 275.8864 0 |
|
|
596 |
## TCACGCATTGTAGATC-1_Assay1 250.58520 319.1566 0 |
|
|
597 |
## CCGAGCTGTGCTTGTC-1_Assay1 474.47505 411.9449 0 |
|
|
598 |
## GCATGGGTACTGACGC-1_Assay1 87.10844 269.6902 0 |
|
|
599 |
## AGTCGGCCCAAACGAC-1_Assay1 215.00861 368.6231 0</code></pre> |
|
|
600 |
<p><br></p> |
|
|
601 |
<p>The arguements of the <strong>vrSegments</strong> functions are |
|
|
602 |
idential to vrCoordinates and return a list of polygon corners |
|
|
603 |
associated with the coordinate system of the coordinates.</p> |
|
|
604 |
<pre class="r watch-out"><code>vrSegments(xenium_data) |
|
|
605 |
vrSegments(xenium_data, assay = "Xenium") |
|
|
606 |
vrSegments(xenium_data, assay = "Assay1") |
|
|
607 |
vrSegments(xenium_data, spatial_name = "main") |
|
|
608 |
vrSegments(xenium_data, spatial_name = "main", reg = TRUE)</code></pre> |
|
|
609 |
<pre><code>## $`171_Assay1` |
|
|
610 |
## id x y |
|
|
611 |
## 1 171 105.25 145.50 |
|
|
612 |
## 2 171 101.75 144.25 |
|
|
613 |
## 3 171 101.50 143.25 |
|
|
614 |
## 4 171 109.75 135.25 |
|
|
615 |
## 5 171 112.00 127.00 |
|
|
616 |
## 6 171 115.50 123.50 |
|
|
617 |
## 7 171 120.00 123.50 |
|
|
618 |
## 8 171 124.25 132.50 |
|
|
619 |
## 9 171 121.00 136.00 |
|
|
620 |
## 10 171 120.25 140.00 |
|
|
621 |
## 11 171 111.25 143.50 |
|
|
622 |
## 12 171 105.50 145.25 |
|
|
623 |
## 13 171 105.25 145.50 |
|
|
624 |
## |
|
|
625 |
## $`180_Assay1` |
|
|
626 |
## id x y |
|
|
627 |
## 14 180 148.25 153.25 |
|
|
628 |
## 15 180 145.75 151.50 |
|
|
629 |
## 16 180 143.25 147.50 |
|
|
630 |
## 17 180 143.25 146.25 |
|
|
631 |
## 18 180 143.00 144.50 |
|
|
632 |
## 19 180 142.50 140.50 |
|
|
633 |
## 20 180 144.25 140.50 |
|
|
634 |
## 21 180 146.25 140.75 |
|
|
635 |
## 22 180 148.50 141.00 |
|
|
636 |
## 23 180 151.00 144.75 |
|
|
637 |
## 24 180 150.50 150.00 |
|
|
638 |
## 25 180 148.75 153.25 |
|
|
639 |
## 26 180 148.25 153.25</code></pre> |
|
|
640 |
<p><br></p> |
|
|
641 |
</div> |
|
|
642 |
<div id="image" class="section level2"> |
|
|
643 |
<h2>Images and Coordinate Systems</h2> |
|
|
644 |
<p>Below we review some of the essential built-in functions to |
|
|
645 |
manipulate and manage images of a VoltRon object as well as the |
|
|
646 |
coordinate systems that are associated with these images.</p> |
|
|
647 |
<p><br></p> |
|
|
648 |
<div id="spatial-coordinate-systems" class="section level3"> |
|
|
649 |
<h3>Spatial Coordinate Systems</h3> |
|
|
650 |
<p>In a VoltRon object, each image has a unique ID which is also |
|
|
651 |
associated with a coordinate (or spatial) system. The names of these |
|
|
652 |
spatial systems can be called using the <strong>vrSpatialNames</strong> |
|
|
653 |
function.</p> |
|
|
654 |
<pre class="r watch-out"><code>vrSpatialNames(visium_data)</code></pre> |
|
|
655 |
<pre><code>## [1] "main"</code></pre> |
|
|
656 |
<p>You can also specify the assay ID or the assay type to call image |
|
|
657 |
names of a subset assays or any assay type (see <a |
|
|
658 |
href="#samplemetadata">Sample Metadata</a>)</p> |
|
|
659 |
<pre class="r watch-out"><code>vrSpatialNames(visium_data, assay = "Visium") |
|
|
660 |
vrSpatialNames(visium_data, assay = "Assay1")</code></pre> |
|
|
661 |
<pre><code>## [1] "main"</code></pre> |
|
|
662 |
<p><br></p> |
|
|
663 |
<p>If you wanna see the list of all spatial systems associated with all |
|
|
664 |
assays of the main assay type, you can call the |
|
|
665 |
<strong>vrMainSpatial</strong> function.</p> |
|
|
666 |
<pre class="r watch-out"><code>vrMainSpatial(visium_data)</code></pre> |
|
|
667 |
<pre><code>## Assay Spatial |
|
|
668 |
## 1 Assay1 main</code></pre> |
|
|
669 |
<p>You can also specify the assay ID or the assay type to call spatial |
|
|
670 |
system names of a subset assays or any assay type (see <a |
|
|
671 |
href="#samplemetadata">Sample Metadata</a>)</p> |
|
|
672 |
<pre class="r watch-out"><code>vrMainSpatial(visium_data, assay = "Visium") |
|
|
673 |
vrMainSpatial(visium_data, assay = "Assay1")</code></pre> |
|
|
674 |
<pre><code>## Assay Spatial |
|
|
675 |
## 1 Assay1 main</code></pre> |
|
|
676 |
<p><br></p> |
|
|
677 |
</div> |
|
|
678 |
<div id="channel-names" class="section level3"> |
|
|
679 |
<h3>Channel Names</h3> |
|
|
680 |
<p>Each spatial system object (vrSpatial) in VoltRon object can also |
|
|
681 |
include a indefinite number of channels which you can get (or request) a |
|
|
682 |
list of for further use.</p> |
|
|
683 |
<pre class="r watch-out"><code>vrImageChannelNames(melc_data) |
|
|
684 |
vrImageChannelNames(melc_data, assay = "MELC") |
|
|
685 |
vrImageChannelNames(melc_data, assay = "Assay1")</code></pre> |
|
|
686 |
<pre><code>## Assay Layer Sample Spatial Channels |
|
|
687 |
## Assay1 MELC Section1 control_case_3 MELC DAPI,CD45</code></pre> |
|
|
688 |
<p><br></p> |
|
|
689 |
</div> |
|
|
690 |
<div id="get-and-set-images" class="section level3"> |
|
|
691 |
<h3>Get and Set Images</h3> |
|
|
692 |
<p>In VoltRon, images can be called specifically, or return as a list. |
|
|
693 |
The return image is of a magick image object (see <a |
|
|
694 |
href="https://cran.r-project.org/web/packages/magick/vignettes/intro.html">magick</a> |
|
|
695 |
package)</p> |
|
|
696 |
<pre class="r watch-out"><code>vrImages(visium_data) |
|
|
697 |
vrImages(visium_data, assay = "Visium") |
|
|
698 |
vrImages(visium_data, assay = "Assay1")</code></pre> |
|
|
699 |
<p><img src="voltronobjects_files/figure-html/unnamed-chunk-36-1.png" width="60%" style="display: block; margin: auto;" /></p> |
|
|
700 |
<!-- <img width="50%" height="50%" src="https://bimsbstatic.mdc-berlin.de/landthaler/VoltRon/Package/images/voltronobjects_HE.png" class="center"> --> |
|
|
701 |
<p><br></p> |
|
|
702 |
<p>Once you know the name of a specific channel, you can the image of a |
|
|
703 |
specific channel by providing the name and the associated channel.</p> |
|
|
704 |
<pre class="r watch-out"><code>vrImages(melc_data, name = "MELC", channel = "DAPI")</code></pre> |
|
|
705 |
<p><img src="voltronobjects_files/figure-html/unnamed-chunk-38-1.png" width="60%" style="display: block; margin: auto;" /></p> |
|
|
706 |
<!-- <img width="50%" height="50%" src="https://bimsbstatic.mdc-berlin.de/landthaler/VoltRon/Package/images/importdata_DAPI.png" class="center"> --> |
|
|
707 |
<p><br></p> |
|
|
708 |
<p>You can set up the main channel as well as the main spatial system |
|
|
709 |
name for later use.</p> |
|
|
710 |
<pre class="r watch-out"><code>vrMainSpatial(melc_data, assay = "Assay1") <- c("MELC", "CD45") |
|
|
711 |
vrImages(melc_data)</code></pre> |
|
|
712 |
<p><img src="voltronobjects_files/figure-html/unnamed-chunk-40-1.png" width="60%" style="display: block; margin: auto;" /></p> |
|
|
713 |
<!-- <img width="50%" height="50%" src="https://bimsbstatic.mdc-berlin.de/landthaler/VoltRon/Package/images/importdata_CD45.png" class="center"> --> |
|
|
714 |
<p><br></p> |
|
|
715 |
<p>You can also resize the images as they are being returned. This is |
|
|
716 |
usually used for visualization purposes and helps speeding up |
|
|
717 |
visualization for large images. This is accomplished with |
|
|
718 |
<strong>scale.perc</strong> arguement.</p> |
|
|
719 |
<pre class="r watch-out"><code>vrImages(melc_data, scale.perc = 25)</code></pre> |
|
|
720 |
<p><br></p> |
|
|
721 |
</div> |
|
|
722 |
<div id="combining-image-channels" class="section level3"> |
|
|
723 |
<h3>Combining Image Channels</h3> |
|
|
724 |
<p>VoltRon even allows manipulation of channel images if you also |
|
|
725 |
provide an associate list of colors.</p> |
|
|
726 |
<pre class="r watch-out"><code>melc_data <- combineChannels(melc_data, |
|
|
727 |
channels = c("DAPI", "CD45"), colors = c("grey", "green"), |
|
|
728 |
channel_key = "combined")</code></pre> |
|
|
729 |
<p>These new images can be stored as new channels within the same image |
|
|
730 |
object, and called later again</p> |
|
|
731 |
<pre class="r watch-out"><code>vrImageChannelNames(melc_data)</code></pre> |
|
|
732 |
<pre><code>## Assay Layer Sample Spatial Channels |
|
|
733 |
## Assay1 MELC Section1 control_case_3 MELC DAPI,CD45,combined</code></pre> |
|
|
734 |
<pre class="r watch-out"><code>vrImages(melc_data, channel = "combined")</code></pre> |
|
|
735 |
<p><img src="voltronobjects_files/figure-html/unnamed-chunk-45-1.png" width="60%" style="display: block; margin: auto;" /></p> |
|
|
736 |
<p><br></p> |
|
|
737 |
</div> |
|
|
738 |
</div> |
|
|
739 |
<div id="feature-matrix-data" class="section level2"> |
|
|
740 |
<h2>Feature Matrix (Data)</h2> |
|
|
741 |
<pre class="r watch-out"><code>vrData(visium_data)[3:8,3:5]</code></pre> |
|
|
742 |
<pre><code>## AAATTACACGACTCTG-1_Assay1 AAGACATACGTGGTTT-1_Assay1 ACCTACTATAAATCTA-1_Assay1 |
|
|
743 |
## Gm19938 0 0 0 |
|
|
744 |
## Gm37381 0 0 0 |
|
|
745 |
## Rp1 0 0 0 |
|
|
746 |
## Sox17 0 1 1 |
|
|
747 |
## Gm37587 0 0 0 |
|
|
748 |
## Gm37323 0 0 0</code></pre> |
|
|
749 |
<pre class="r watch-out"><code>vrData(visium_data, norm = TRUE)[3:8,3:5]</code></pre> |
|
|
750 |
<pre><code>## AAATTACACGACTCTG-1_Assay1 AAGACATACGTGGTTT-1_Assay1 ACCTACTATAAATCTA-1_Assay1 |
|
|
751 |
## Gm19938 0 0.0000000 0.0000000 |
|
|
752 |
## Gm37381 0 0.0000000 0.0000000 |
|
|
753 |
## Rp1 0 0.0000000 0.0000000 |
|
|
754 |
## Sox17 0 0.2732722 0.2164184 |
|
|
755 |
## Gm37587 0 0.0000000 0.0000000 |
|
|
756 |
## Gm37323 0 0.0000000 0.0000000</code></pre> |
|
|
757 |
<p><br></p> |
|
|
758 |
</div> |
|
|
759 |
<div id="embedding" class="section level2"> |
|
|
760 |
<h2>Embeddings</h2> |
|
|
761 |
<p>You can parse and even set individual embedding elements in a VoltRon |
|
|
762 |
object.</p> |
|
|
763 |
<pre class="r watch-out"><code>vrEmbeddingNames(xenium_data)</code></pre> |
|
|
764 |
<pre><code>## [1] "pca" "umap"</code></pre> |
|
|
765 |
<p>You can use these names of get the associated embedding dataset from |
|
|
766 |
the object.</p> |
|
|
767 |
<pre class="r watch-out"><code>vrEmbeddings(xenium_data, type = "umap")</code></pre> |
|
|
768 |
<pre><code>## x y |
|
|
769 |
## 171_Assay1 -7.110343 0.451607 |
|
|
770 |
## 180_Assay1 5.333756 3.896294 |
|
|
771 |
## 182_Assay1 3.805085 4.581084 |
|
|
772 |
## 185_Assay1 5.330851 3.870111 |
|
|
773 |
## 197_Assay1 -4.397479 2.763229 |
|
|
774 |
## 206_Assay1 -1.753468 3.973698</code></pre> |
|
|
775 |
<p>You can also set and create new embedding elements in the voltron |
|
|
776 |
object. In this case, you have to make sure that the row names should |
|
|
777 |
match with the targeted spatial points.</p> |
|
|
778 |
<pre class="r watch-out"><code>new_umap_data <- vrEmbeddings(xenium_data, type = "umap") |
|
|
779 |
vrEmbeddings(xenium_data, type = "new_umap") <- new_umap_data*2</code></pre> |
|
|
780 |
<p>Now we can observe changes to the new embedding data.</p> |
|
|
781 |
<pre class="r watch-out"><code>vrEmbeddings(xenium_data, type = "new_umap")</code></pre> |
|
|
782 |
<pre><code>## x y |
|
|
783 |
## 171_Assay1 -14.220687 0.903214 |
|
|
784 |
## 180_Assay1 10.667511 7.792587 |
|
|
785 |
## 182_Assay1 7.610170 9.162168 |
|
|
786 |
## 185_Assay1 10.661703 7.740223 |
|
|
787 |
## 197_Assay1 -8.794958 5.526458 |
|
|
788 |
## 206_Assay1 -3.506937 7.947396</code></pre> |
|
|
789 |
<p>You can choose individual assay names or assay classes.</p> |
|
|
790 |
<pre class="r watch-out"><code>vrEmbeddings(xenium_data, type = "umap", assay = "Xenium") |
|
|
791 |
vrEmbeddings(xenium_data, type = "pca", assay = "Assay1")</code></pre> |
|
|
792 |
<p><br></p> |
|
|
793 |
</div> |
|
|
794 |
<div id="subsetting-voltron-objects" class="section level2"> |
|
|
795 |
<h2>Subsetting VoltRon objects</h2> |
|
|
796 |
<p><br></p> |
|
|
797 |
<div id="sampleassay" class="section level3"> |
|
|
798 |
<h3>sample/assay</h3> |
|
|
799 |
<p>VoltRon object can be subsetted in a variety of ways using assay |
|
|
800 |
names, sample names, spatial point names, features (e.g. gene), image |
|
|
801 |
coordinates (crop boxes or bounding boxes) as well as interactively.</p> |
|
|
802 |
<pre class="r watch-out"><code>visium_data_subset <- subset(visium_data, assays = "Assay1")</code></pre> |
|
|
803 |
<pre class="r watch-out"><code>visium_data_subset <- subset(visium_data, samples = "Anterior1") |
|
|
804 |
visium_data_subset</code></pre> |
|
|
805 |
<pre><code>## VoltRon Object |
|
|
806 |
## Anterior1: |
|
|
807 |
## Layers: Section1 |
|
|
808 |
## Assays: Visium(Main) |
|
|
809 |
## Features: RNA(Main)</code></pre> |
|
|
810 |
<p><br></p> |
|
|
811 |
</div> |
|
|
812 |
<div id="spatial-points" class="section level3"> |
|
|
813 |
<h3>spatial points</h3> |
|
|
814 |
<p>You can use a list of spatial points (typically using |
|
|
815 |
<strong>vrSpatialPoints</strong> function, see <a |
|
|
816 |
href="#spatialpoints">vrSpatialPoints</a>)</p> |
|
|
817 |
<pre class="r watch-out"><code>selected_points <- vrSpatialPoints(visium_data) |
|
|
818 |
selected_points[1:20]</code></pre> |
|
|
819 |
<pre><code>## [1] "AAAGGCTCTCGCGCCG-1_Assay1" "AAATGGCCCGTGCCCT-1_Assay1" "AAATTACACGACTCTG-1_Assay1"</code></pre> |
|
|
820 |
<pre class="r watch-out"><code>visium_data_subset <- subset(visium_data, spatialpoints = selected_points[1:20]) |
|
|
821 |
visium_data_subset</code></pre> |
|
|
822 |
<pre><code>## VoltRon Object |
|
|
823 |
## Anterior1: |
|
|
824 |
## Layers: Section1 |
|
|
825 |
## Assays: Visium(Main) |
|
|
826 |
## Features: RNA(Main)</code></pre> |
|
|
827 |
<p><br></p> |
|
|
828 |
</div> |
|
|
829 |
<div id="features" class="section level3"> |
|
|
830 |
<h3>features</h3> |
|
|
831 |
<p>You can select a few number of features and subset the features given |
|
|
832 |
this list. However, it would only subset the main assay (see <a |
|
|
833 |
href="#assays">vrMainAssay</a>)</p> |
|
|
834 |
<pre class="r watch-out"><code>selected_features <- vrFeatures(visium_data) |
|
|
835 |
selected_features[1:20]</code></pre> |
|
|
836 |
<pre><code>## [1] "Xkr4" "Gm1992" "Gm19938" "Gm37381" "Rp1" "Sox17" "Gm37587" "Gm37323" "Mrpl15" "Lypla1" |
|
|
837 |
## [11] "Tcea1" "Rgs20" "Gm16041" "Atp6v1h" "Oprk1" "Npbwr1" "Rb1cc1" "4732440D04Rik" "Alkal1" "St18"</code></pre> |
|
|
838 |
<pre class="r watch-out"><code>visium_data_subset <- subset(visium_data, features = selected_features[1:20]) |
|
|
839 |
vrFeatures(visium_data_subset)</code></pre> |
|
|
840 |
<pre><code>## [1] "Xkr4" "Gm1992" "Gm19938" "Gm37381" "Rp1" "Sox17" "Gm37587" "Gm37323" "Mrpl15" "Lypla1" |
|
|
841 |
## [11] "Tcea1" "Rgs20" "Gm16041" "Atp6v1h" "Oprk1" "Npbwr1" "Rb1cc1" "4732440D04Rik" "Alkal1" "St18"</code></pre> |
|
|
842 |
<p><br></p> |
|
|
843 |
</div> |
|
|
844 |
<div id="interactive-subsetting" class="section level3"> |
|
|
845 |
<h3>Interactive subsetting</h3> |
|
|
846 |
<p>VoltRon allows interactively subsetting spatial data. Using the |
|
|
847 |
arguement <strong>interactive = TRUE</strong>, a mini Shiny app is |
|
|
848 |
triggered where users can select a bounding box to crop the spatial |
|
|
849 |
data.</p> |
|
|
850 |
<pre class="r watch-out"><code>visium_data_subset_info <- subset(visium_data, interactive = TRUE) |
|
|
851 |
visium_data_subset <- visium_data_subset_info$subsets[[1]]</code></pre> |
|
|
852 |
<pre><code>VoltRon Object |
|
|
853 |
Anterior1_subset: |
|
|
854 |
Layers: Section1 |
|
|
855 |
Assays: Visium(Main) </code></pre> |
|
|
856 |
<pre class="r watch-out"><code>vrImages(visium_data_subset)</code></pre> |
|
|
857 |
<p><br></p> |
|
|
858 |
</div> |
|
|
859 |
</div> |
|
|
860 |
<div id="visualization" class="section level2"> |
|
|
861 |
<h2>Visualization</h2> |
|
|
862 |
<p>VoltRon provides visualization utilities for both spatial and |
|
|
863 |
embedding level visualizations.</p> |
|
|
864 |
<p><br></p> |
|
|
865 |
<div id="spatial-plots" class="section level3"> |
|
|
866 |
<h3>Spatial Plots</h3> |
|
|
867 |
<p><strong>vrSpatialPlot</strong> is the main function for visualize |
|
|
868 |
labels and identities of cells. This information is parsed from the |
|
|
869 |
Metadata of the main assay (see <a href="#assays">vrMainAssay</a>). The |
|
|
870 |
users can also specify the assay.</p> |
|
|
871 |
<pre class="r watch-out"><code>vrSpatialPlot(xenium_data, group.by = "clusters")</code></pre> |
|
|
872 |
<p><img width="50%" height="50%" src="https://bimsbstatic.mdc-berlin.de/landthaler/VoltRon/Package/images/voltronobjects_sp.png" class="center"></p> |
|
|
873 |
<p><br></p> |
|
|
874 |
<p>You can also visualize the segments of spatial points and even get |
|
|
875 |
the segments transparent</p> |
|
|
876 |
<pre class="r watch-out"><code>vrSpatialPlot(xenium_data, group.by = "clusters", plot.segments = TRUE, alpha = 0.6)</code></pre> |
|
|
877 |
<p><img width="50%" height="50%" src="https://bimsbstatic.mdc-berlin.de/landthaler/VoltRon/Package/images/voltronobjects_spsegment.png" class="center"></p> |
|
|
878 |
<p><br></p> |
|
|
879 |
<p>The background color can be set to any color.</p> |
|
|
880 |
<pre class="r watch-out"><code>vrSpatialPlot(xenium_data, group.by = "clusters", plot.segments = TRUE, |
|
|
881 |
background.color = "white")</code></pre> |
|
|
882 |
<p><img width="50%" height="50%" src="https://bimsbstatic.mdc-berlin.de/landthaler/VoltRon/Package/images/voltronobjects_spback.png" class="center"></p> |
|
|
883 |
<p><br></p> |
|
|
884 |
<p>In cases where there are multiple coordinate systems, you can get the |
|
|
885 |
background set to the name of the image (or coordinate system). You can |
|
|
886 |
get the name of these images from <a |
|
|
887 |
href="#image">vrSpatialNames</a>.</p> |
|
|
888 |
<p>If also want to select a channel from the same coordinate system, you |
|
|
889 |
can set background arguement as a vector of 2 where first is the name of |
|
|
890 |
the image (coordinate system) and the other would be channel name. You |
|
|
891 |
can get the name of these channels from <a |
|
|
892 |
href="#image">vrImageChannelNames</a>.</p> |
|
|
893 |
<pre class="r watch-out"><code>vrSpatialPlot(xenium_data, group.by = "clusters", plot.segments = TRUE, |
|
|
894 |
spatial = "main") |
|
|
895 |
vrSpatialPlot(xenium_data, group.by = "clusters", plot.segments = TRUE, |
|
|
896 |
spatial = "main", channel = "DAPI")</code></pre> |
|
|
897 |
<p><br></p> |
|
|
898 |
<p>If the visualized assay is of a type “spot”, you can crop the image |
|
|
899 |
to encapsulate the smallest subset that include all spots.</p> |
|
|
900 |
<pre class="r watch-out"><code>vrSpatialPlot(visium_data, group.by = "Sample", crop = TRUE)</code></pre> |
|
|
901 |
<p><img width="50%" height="50%" src="https://bimsbstatic.mdc-berlin.de/landthaler/VoltRon/Package/images/voltronobjects_spcrop.png" class="center"></p> |
|
|
902 |
<p><br></p> |
|
|
903 |
<p>The <strong>vrSpatialFeaturePlot</strong> functions the same way as |
|
|
904 |
vrSpatialPlot but requires extra arguements such as |
|
|
905 |
<strong>features</strong> for selecting features, <strong>norm</strong> |
|
|
906 |
for normalized expression (default), and <strong>log</strong> for log |
|
|
907 |
transformed counts.</p> |
|
|
908 |
<pre class="r watch-out"><code>vrSpatialFeaturePlot(visium_data, features = "Count") |
|
|
909 |
vrSpatialFeaturePlot(visium_data, features = "Stat1", norm = TRUE)</code></pre> |
|
|
910 |
<p><img width="100%" height="100%" src="https://bimsbstatic.mdc-berlin.de/landthaler/VoltRon/Package/images/voltronobjects_spfeature.png" class="center"></p> |
|
|
911 |
<p><br></p> |
|
|
912 |
<p>For all variations of <strong>vrSpatialPlot</strong> and |
|
|
913 |
<strong>vrSpatialFeaturePlot</strong> functions above, you can specifiy |
|
|
914 |
the assay names or assay class.</p> |
|
|
915 |
<pre class="r watch-out"><code>vrSpatialPlot(visium_data, assay = "Visium", plot.segments = TRUE) |
|
|
916 |
vrSpatialPlot(visium_data, assay = "Assay1", plot.segments = TRUE) |
|
|
917 |
vrSpatialFeaturePlot(visium_data, assay = "Visium", features = "Count") |
|
|
918 |
vrSpatialFeaturePlot(visium_data, assay = "Assay1", features = "Count")</code></pre> |
|
|
919 |
<p><br></p> |
|
|
920 |
</div> |
|
|
921 |
<div id="spatial-plots-multi-layer" class="section level3"> |
|
|
922 |
<h3>Spatial Plots (Multi-Layer)</h3> |
|
|
923 |
<p><strong>vrSpatialPlot</strong> function can be paired with the |
|
|
924 |
<strong>addSpatialLayer</strong> function to add additional assays of |
|
|
925 |
the same spatial coordinate system as the original assay. We use the |
|
|
926 |
piping operator “|>” to connect to functions which overlays the |
|
|
927 |
results of the first image with the second. |
|
|
928 |
<strong>addSpatialLayer</strong> will check if two assays are within the |
|
|
929 |
same tissue block and coordinate system, and will overlay these assays |
|
|
930 |
if thats the case.</p> |
|
|
931 |
<p>This utility can be used to visualize molecules along with cell |
|
|
932 |
segments. Here we can also color each individual molecule (gene) |
|
|
933 |
type.</p> |
|
|
934 |
<pre class="r watch-out"><code>library(ggnewscale)</code></pre> |
|
|
935 |
<pre class="r watch-out"><code>vrSpatialPlot(merged_object, plot.segments = TRUE, group.by = "clusters") |> |
|
|
936 |
addSpatialLayer(merged_object, assay = "Assay2", group.by = "gene", alpha = 1, |
|
|
937 |
colors = list(KRT15 = "blue", KRT14 = "green"))</code></pre> |
|
|
938 |
<pre><code>## Warning: Duplicated `override.aes` is ignored.</code></pre> |
|
|
939 |
<p><img src="voltronobjects_files/figure-html/unnamed-chunk-73-1.png" width="60%" style="display: block; margin: auto;" /></p> |
|
|
940 |
<p><br></p> |
|
|
941 |
<p>You can also visualize the segments that represents annotations of |
|
|
942 |
the tissue sections along with the cells.</p> |
|
|
943 |
<pre class="r watch-out"><code>vrSpatialPlot(merged_object, plot.segments = FALSE, group.by = "clusters") |> |
|
|
944 |
addSpatialLayer(merged_object, assay = "Assay3", group.by = "Region", alpha = 0.3, |
|
|
945 |
color = list(Region1 = "blue", Region2 = "yellow"))</code></pre> |
|
|
946 |
<pre><code>## Warning: Duplicated `override.aes` is ignored.</code></pre> |
|
|
947 |
<p><img src="voltronobjects_files/figure-html/unnamed-chunk-74-1.png" width="60%" style="display: block; margin: auto;" /></p> |
|
|
948 |
<p><br></p> |
|
|
949 |
</div> |
|
|
950 |
<div id="embedding-plots" class="section level3"> |
|
|
951 |
<h3>Embedding Plots</h3> |
|
|
952 |
<p>Dimensional reduction and embedding features are also possible for |
|
|
953 |
the VoltRon objects.</p> |
|
|
954 |
<pre class="r watch-out"><code>vrEmbeddingPlot(xenium_data, embedding = "umap", group.by = "clusters", label = T)</code></pre> |
|
|
955 |
<p><img width="50%" height="50%" src="https://bimsbstatic.mdc-berlin.de/landthaler/VoltRon/Package/images/voltronobjects_embed.png" class="center"></p> |
|
|
956 |
<p><br></p> |
|
|
957 |
<p>The <strong>vrEmbeddingFeaturePlot</strong> functions the same way as |
|
|
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vrEmbeddingPlot but requires extra arguements such as |
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<strong>features</strong> for selecting features, <strong>norm</strong> |
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for normalized expression (default), and <strong>log</strong> for log |
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transformed counts.</p> |
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<pre class="r watch-out"><code>vrEmbeddingFeaturePlot(xenium_data, embedding = "umap", features = "Count") |
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vrEmbeddingFeaturePlot(xenium_data, embedding = "umap", features = "KRT5", norm = FALSE)</code></pre> |
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<p><img width="100%" height="100%" src="https://bimsbstatic.mdc-berlin.de/landthaler/VoltRon/Package/images/voltronobjects_embedfeature.png" class="center"></p> |
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<p><br></p> |
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<p>For all variations of <strong>vrEmbeddingPlot</strong> and |
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<strong>vrEmbeddingFeaturePlot</strong> functions above, you can |
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968 |
specifiy the assay names or assay class.</p> |
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969 |
<pre class="r watch-out"><code>vrEmbeddingPlot(xenium_data, assay = "Xenium", embedding = "umap") |
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vrEmbeddingPlot(xenium_data, assay = "Assay1", embedding = "umap") |
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vrEmbeddingFeaturePlot(xenium_data, assay = "Xenium", embedding = "umap", features = "Count") |
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vrEmbeddingFeaturePlot(xenium_data, assay = "Assay1", embedding = "umap", features = "Count")</code></pre> |
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</div> |
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