Project description:The Pan-Cancer Analysis of Whole Genomes (PCAWG) study is an international collaboration to identify common patterns of mutation in more than 2,800 cancer whole genomes from the International Cancer Genome Consortium. Building upon previous work which examined cancer coding regions, this project is exploring the nature and consequences of somatic and germline variations in both coding and non-coding regions, with specific emphasis on cis-regulatory sites, non-coding RNAs, and large-scale structural alterations. Read more on the <a href=\"https://dcc.icgc.org/pcawg\" target=\"_blank\">project website</a>.<br>This is a subset featuring RNA-seq transcription profiling data of 27 cancer subtypes in 19 tissues. Some donors have matched normal tissue. As general reference, a subset of normal tissue samples from the GTEx project were included in this experiment.
Project description:The Pan-Cancer Analysis of Whole Genomes (PCAWG) study is an international collaboration to identify common patterns of mutation in more than 2,800 cancer whole genomes from the International Cancer Genome Consortium. Building upon previous work which examined cancer coding regions, this project is exploring the nature and consequences of somatic and germline variations in both coding and non-coding regions, with specific emphasis on cis-regulatory sites, non-coding RNAs, and large-scale structural alterations. Read more on the <a href=\"https://dcc.icgc.org/pcawg\" target=\"_blank\">project website</a>.<br>This is a subset featuring RNA-seq transcription profiling data of 27 cancer subtypes in 19 tissues. Some donors have matched normal tissue.<br>This is the alternative view of the experiment for Expression Atlas to show gene expression per donor.
Project description:Defining the subcellular distribution of all human proteins and its remodeling across cellular states remains a central goal in cell biology. Here, we present a high-resolution strategy to map subcellular organization using organelle immuno-capture coupled to mass spectrometry. We apply this workflow to a cell-wide collection of membranous and membrane-less compartments. A graph-based analysis reveals the subcellular localization of over 7,600 proteins, defines spatial networks, and uncovers interconnections between cellular compartments. Our approach can be deployed to comprehensively profile proteome remodeling during cellular perturbation. By characterizing the cellular landscape following hCoV-OC43 viral infection, we discover that many proteins are regulated by changes in their spatial distribution rather than by changes in abundance. Our results establish that proteome-wide analysis of subcellular remodeling provides unique insights for the elucidation of cellular responses, uncovering an essential role for ferroptosis in OC43 infection. Our dataset can be explored at organelles.czbiohub.org.