Welcome to a Synthesize Bio notebook!

These are notebooks that allow you to create custom analysis on any datasets. You can then re-run any notebook on new data.

This tutorial teaches you about some of the magic functionality that makes our notebooks unique.

This is an R notebook. Please also try a Python notebook!

What Makes This Notebook Different?

• Special functions for easily displaying interactive plots and tables
• Automatic data import as an SummarizedExperiment object
• Notebook sharing and re-running

Built in functions for this notebook environment

plot |> set_plot()

Will render any plotly or ggplot2 plot as a ploty plot.
Base R plots do not render interactively, but can still be displayed.

data.frame |> set_table()

Will render any data.frame or data.table as a paginated table.

"markdown text" |> set_markdown()

Will show formatted markdown text.

See the code chunk below for example usage.

Data is Loaded as a SummarizedExperiment Object

See the below chunk for how the summarized experiment object is loaded

This offers several advantages:

• Sample-level metadata is available in colData().
• Gene-level metadata (e.g., mapping identifiers) is available in rowData().
• Raw counts are stored in assay() and TPM in assay()$TPM.

See the Summarized Experiment docs to learn more!

When working with SummarizedExperiment objects, keep in mind that colData() and rowData() objects are not data.frame objects and so they need to be converted to data.frame for set_table() to work

Editing

• You can freely modify this notebook.
• Add, edit, or rearrange code and text chunks as needed.

Editing Code Chunks

• Toggle "View code" in the header to display all code.
• Run individual chunks by clicking the ► button in the top-left corner of each chunk.
• Execute the entire notebook by clicking ► in the header.

Code Editor Shortcuts

This notebook supports VS Code-style shortcuts for efficient editing:

• Press F1 to open the command palette and view all commands.
• Comment/uncomment a code selection with Command (⌘) + /.
• Indent code with Command (⌘) + ].
• Move chunks using the Edit menu in the top-left corner of each chunk.

Sharing and Re-running

Share your notebook using the 🌍 Share button in the top-right menu to generate a read-only link for colleagues.

You can also use the top-right menu to:

• Create a copy of the notebook.
• Edit Data and re-run the notebook on different datasets.