FAQ

1\ what is mavatar discovery? mavatar discovery is a licensed, self service data driven research platform designed for pharmaceutical companies, researchers, cros, and academia through mavatar discovery, users access an extensive catalogue of integrated bioinformatic resources each resource is trained on up to hundreds of datasets, enabling powerful insights into tissue centric disease pathogenesis, patient stratification and treatment mechanisms of action 2\ what kind of data does mavatar discovery provide access to? the platform contains an extensive catalogue of dina (deep integrated network analysis) resources from a wide spectrum of tissues, and disease specific resources in each these represent strongly preserved gene gene interactions, with readily available detailed functional characterization, based on a database of curated meta data 3\ describe how the data process works? at the core of mavatar discovery is dina (deep integrated network analysis), our proprietary framework built on 20+ years of scientific expertise dina integrates and analyzes thousands of transcriptomic datasets to model disease mechanisms at a systems level—delivering gene level networks by tissue and disease functional enrichment tools with full traceability back to raw data overlapping networks across diseases for broader insights you get curated, structured results—not just raw data or pre packaged database queries new features and capabilities are added continuously as we shape the future of research our approach also ensures high reproducibility, enables more accurate translation between animal and human studies, allows us to compare different diseases affecting the same tissue, and how the same disease is present in different tissues, etc 4\ in what formats are the data driven insights and reports provided? user can export their findings to png and svg (vector graphics) they can also customize coloring and layout, including pre set themes that can match publication graphic requirements, etc 5\ can users upload and integrate their own data? yes, users can securely upload gene sets and their differential regulations for sub setting local networks 6\ how fast can users get insights? depending on the complexity of the query, results can be generated in mere seconds, significantly reducing the time required for traditional analysis 7\ how do i generate a new graph (visualize a sub graph)? conduct a new search by clicking the “generate graph” button in the top left hand corner of the canvas, selecting a tissue, general or disease specific network model submit your gene names, choose from our suggested gene sets, search by drug, or search for top interactions in the selected model 8\ i cannot find my desired tissue type or condition how do i request a new network? is the tissue / disease you are interested in not precalculated in mavatar discovery yet? contact us and we will be happy to arrange a project together for a custom data survey and network construction 9\ what is the canvas in mavatar discovery? the space where your network is generated is called the canvas – this is where you will explore & discover new connections between genes 10\ what is a “card” in mavatar discovery? floating on top of the canvas mavatar discovery presents cards with various categories of information a card will always contain information about the network generated in the canvas – eg about the genes, edges or other information regarding what you see in the canvas 11\ how can i explore the highest normalized t values of a full network without selecting a gene? at the top of the generate graph window, click "top interactions" and choose the number of strongest edges you want to generate the network for 12\ how does the normalized t value distribution and filtering feature work? after an initial network has been drawn, a histogram of the edge weights among the edges drawn can be seen in the filter card adjust the sliders to limit the edges further within this edge weight span 13\ where can i find a list of all gses available in the platform, and how does it work? we provide a description of datasets contributing to each network further information on datasets contributing to specific edges can be found in the dina functional annotation card connected to the graph 14\ can i search datasets by drug treatment, and how does it work? yes, you can and as time passes we aim to expand the list of available drugs right now, you can find limited search by drug information by clicking “generate graph” and search by drug in the “generate graph” modal 15\ how do i search using a list of genes? upload the gene list text file instead of manually adding genes in the search card 16\ explain the gene information card detailed descriptions of genes? when clicking a gene in the drawn network, this card provides a description and some synonyms of this gene, along with the gene type as defined by ensembl 17\ can i search for genes by different tagging standards (such as symbol or ensembl id)? yes mavatar discovery supports both symbol and ensembl id 18\ how can i save my search or filter settings for later? in the top right hand corner of your screen, just above the canvas you have the option to save the current generated network to find your saved searches, simply click the dropdown of saved searches in the top right hand corner of the canvas 19\ what is the heatmap card, and what does it explain? the heatmap displays expression levels from an example dataset of the ones that contributed to the present network only genes appearing in the drawn network are included in the heatmap genes and samples are clustered (upgma, euclidean distance) and samples are annotated based on our curated metadata 20\ what is the umap card, and what does it explain? the umap displays coordinates in umap space, of cells from an example single cell rna sequencing dataset from the same tissue as the tissue of the current network cells can be coloured by a gene’s expression level by clicking that gene node in the drawn network 21\ how can i compare two overlapping or combined networks? drawing two networks at once (toggle “secondary” in the generate graph modal) draws the edges from both networks, in different colours this provides an overview of their overlap in addition, any single network drawn will be compared to our other networks (using mantel tests on the node node distances) – and the results visualised in the card “dina network similarity” this provides a measure of topology overlap for this gene set in pairs of networks 22\ what is the gene type filter? the gene type filter gives you the option to filter your analysis by gene/transcript biotype classification provided by ensembl https //www ensembl org/info/genome/genebuild/biotypes html 23\ how does the gene file search work? genes can be matched using a gene file files can be text based ( txt, csv) or excel spreadsheet ( xlsx) templates can be found in https //discovery demo mavatar com/genefiletemplates zip the archive contain a readme txt with general instructions as well as four gene files in the supported formats 24\ can i use mavatar's resources to create my own custom dina resource? yes, you can we employ our pipeline to create a custom dina resource for any combination of public domain, or user provided datasets this will allow a user with a novel dataset from any disease domain to be integrated and compared to existing datasets from the same disease domain or tissue context the most seamless custom dina resource integration requires rna sequencing data (bulk or single cell), but our pipeline is compatible with proteomic or any quantitative data contact https //www mavatar com/contact for more information