Get Started with Pluto Programs

In this quick-start guide, you'll learn how to log into your Lab Space, create your first program, and add a dataset. Feel free to use the in-app chat in Pluto if you run into any questions along the way!

Karly Fear
22 steps

Welcome to Pluto

To get started, check your inbox for the invitation email. Click the "Accept Invitation" button in the email and sign up for a new account, or log in if you've already created one.

Once logged in, navigate to your LabSpace (https://app.pluto.bio/labspace). Here, you’ll find a dashboard to later view active programs in your Organization, along with customizable widgets available in the ‘Snapshot’ section. Your dashboard may look a little empty when you’re just starting out, but soon it will be full of stats including number of datasets, analysis spaces, and plots!

Creating a Program

Every dataset, analysis, and visualization is nested in **Programs**, which are the highest level of organization in Pluto. Programs are specifically designed to keep these assets connected within a single platform. As a result, scientific leaders are given a continuous, traceable view of what work is happening, what questions each asset is answering, and what program-level decisions these are moving forward. Click on “+ Program” in the Programs overview page to create a new program.

Give your program an informative name (typically, the way it’s most commonly referred to internally) and select from one of the available program types created by your company admins.

A program’s metadata provides valuable context for all downstream activities performed by your team so it is important to fill out as much information as possible. The **owner** is the user that serves as the program lead and primary point of contact. To select **Therapeutic Area(s)**, use the dropdown to select one or multiple options. This field is used for helping filter programs, datasets, and analyses later on. Similarly, the dropdown for **Modalities** allows you to select 1 modality being used by the program, or add multiple modalities if several are being explored or combined.

The field for **Target declared** accepts Yes or No. If the program is still narrowing in on a target (e.g., in early target discovery, identification, and validation), this field should be set to ‘No’ so that Pluto can emphasize analyses that explore multiple targets and help rank, score, and prioritize a list of targets for an interactive narrowing process. For programs that have declared a target, this field should be set to ‘Yes’ so that Pluto can suggest analyses that increase confidence through orthogonal angles, such as therapeutic framing, disease relevance, mechanistic and functional evidence, preclinical model alignment, patient population, and more.

Adding a new dataset

A **dataset** contains the assay and sample data for an experiment. You can create or convert datasets in a few ways. Navigate to the Datasets overview page from the lefthand side navigation pane.

From this page, you can view existing Internal program data, imported Global Data Commons (i.e., GEO datasets), or you can click “+ Dataset” to create a new dataset. You may also navigate to the Dataset registry section within an existing program and convert a dataset, search available datasets, or add a new dataset. Note: Click on “+ GEO Import” to request for a GEO dataset to be imported by our team.

Not seeing an experiment type you need? Reach out to your Pluto rep any time to discuss upgrading to another plan

Each dataset has fields that map to existing programs. Along with naming the dataset, you will select the Program, Folder, Assay type, and Organism. You may optionally include a data source by clicking on the dropdown.

Tip! Pluto experiment tiles display the organism and experiment type by default so there's no need to include things like "human" or "RNA-seq" in the experiment's name

Once the dataset is created, you will be directed to add the assay and sample data. Depending on whether raw or processed data was uploaded, a pipeline may be configured and started for pre-processing of raw FASTQ files. Until assay and sample data have been uploaded (and a pipeline has been configured, if applicable), yellow 'in-progress' status icons will appear next to each of the data setup steps.

Datasets accept either raw or processed data for most experiment types; simply drag-and-drop your files into the appropriate windows. When uploading assay and sample data, it is important to note the formatting required per experiment type. Access our in-app formatting guides during each of these upload steps, or take a look at our [Data Upload Overview](https://pluto-bio-knowledge-base.help.usepylon.com/articles/2937074029) article for more detailed information. Once your assay and sample data have been uploaded (and a pipeline has been configured, if applicable), you'll notice that the status cues are now green.

Starting an analysis space

Once a dataset is ready for analysis, you will have the option to add the dataset to an existing analysis space or start a new analysis space.

When creating a new analysis space, a name is required. While optional, it is helpful to write out the driving goal or hypothesis that this space will explore.

Linking datasets to an analysis space

To add a dataset to an existing analysis space, navigate to the Analysis space registry and click into the Analysis space canvas of interest.

To view datasets that are already linked to a specific analysis space, click on the Data sources icon in the Canvas toolbar.

Scroll to the bottom of the pop-up window to see the "+ Link a dataset" option, which enables you to search datasets by name or PLX ID.

In addition to searching datasets available to you in your organization, Pluto has over 14k public experiments accessible in the Global Data Commons. Any of these experiments can be linked to an analysis space after clicking on Global Data Commons in the 'Link datasets' window and searching by keyword or PLX ID. Multiple datasets can be linked at once with a simple click of a button! Note: you may also perform a similar search of public experiment by accessing the Global Data Commons by accessing the Datasets tab in the navigation pane on the lefthand side of the app.

Analyzing a dataset

Once the dataset is linked to an analysis space, you can click on “Create new analysis” underneath the dataset of interest, and this will open the analysis catalog.

Select the analysis you’d like to run, and click on “+ Create analysis” to access the relevant parameters.

Once created, you can customize your plots by clicking the ‘...’ in the upper right of any plot, and navigating to the ‘Plot’ tab to make your changes. Once you apply your edits, click on ‘Save changes’ to see the customized plot in your analysis space.

Pluto supports a wide variety of analysis types, and the plots you'll create are highly customizable. Check out our help docs at <https://help.pluto.bio> for how-to guides and inspiration!

Inviting collaborators

Invite collaborators to your organization from the Team tab: <https://app.pluto.bio/team>

Once the collaborator has been added to your organization, you can invite them to individual programs by navigating to the Users tab within the program and selecting their email from the User dropdown.