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    Imagine you’re a researcher who’s interested in a specific topic within single-cell genomics – for example, HIV. To make your own research more thoughtful and impactful, it’s often useful to survey the existing datasets that involve HIV, to get a sense of what questions people are asking about HIV, and what the answers are so far. Or, you might be interested in gathering data on a specific cell type or organ. Gathering data of the same type, across multiple datasets, could help you build a cohort of data – you’ll then be able to run analyses across these datasets, with more statistical power to pick up small effects than if you were to analyze a single dataset. Doing so also allows you to find results that are more robust to the smaller details that set studies apart, such as the specific organisms that were sampled. 

    While gathering data from...


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    Which color scale do you think that SCP should use by default? Take this 2-minute survey to let us know!

     

    One of the Single Cell Portal’s goals is to build interactive plots that make it easy for scientists to explore the patterns in single-cell data. Given that, we’re always looking for ways to make our plots easier to interpret. As anyone who has made a paper figure can attest, there is a real art to this -- how do you make the data “sing” so that a viewer can instantly see the interesting patterns that it holds, while remaining honest about the complexity and noise in the data? Recently, we made some changes that improve the data’s ability to sing on SCP. Specifically, we updated the color scales that we use to plot gene expression data. 

     

     

     

    To understand the art behind plotting gene expression data well, it’s useful...

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    Have you ever visited the Single Cell Portal to search for interesting data, and gotten lost in all of the studies? Or, have you ever wished that you could easily point another researcher toward all of the data that you have on SCP, without sending them a separate link for each study?

    If either of these stories sounds familiar, you can now take advantage of SCP's study collections. Collections are curated sets of studies that share a common topic or research group. If you've come to SCP to learn more about a specific research topic or group, browse through these collections to narrow your search down to the studies you're most likely to be interested in. And if you -- or your lab -- have several studies in SCP, you can create a collection in order to share your work more easily. Creating a collection simply opens a separate...

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    Submitting your findings for publication can be one of the most stressful stages in the research lifecycle. Often, this is because the submission process requires you to manage several logistical tasks beyond the actual paper-writing. For example, more and more journals require a link to a repository where reviewers can explore your data as they comb through your manuscript. However, you might not be ready to share your data with the world until the paper has passed this review.

    To ease this process, we’ve created a way to grant reviewers anonymous access to your SCP study while it is still private. Once you’ve activated access for reviewers, SCP will generate a unique URL and PIN, which your reviewers can use to visualize and explore your data (but not download it). You can also control when this access expires, or reset the access information at any time...

  • SCP now supports spatial transcriptomics data! These data help researchers understand how patterns in genetic expression or cell types are distributed in the tissue. For example, are cells with similar genetic expression profiles clustered close together in the tissue, or dispersed throughout? You can explore these spatial distributions alongside other plots, like gene expression clustering plots -- check out an example study here

    If you have spatial transcriptomics data to share through SCP, you can upload the spatial coordinates of your samples through our upload wizard. 

     

     

     

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    This look into spatial data is part of a series of announcements where we’ll shine a light on previously-hidden features of SCP. These will include:

    • Granting study access to anonymous reviewers
    • Study “collections”
    • An ideogram viewer to discover related genes
    • Selecting customized subsets of data from a plot
    • Our new requirement to include raw counts matrices when you upload data
    • Adding images to your study's description

    We’ll also highlight...