Visualization

Title	Description	Input Data
Wally visualizations	This Capsule creates a genomic alignment plot of reads in a specified region mapped to a reference. The visualization of genomic alignments was heavily inspired by IGV, and customized to visualize structural variation and CNVs.	Genome .fasta reference and .fai file .bam files
Samplot Visualization (from coordinates)	a command line tool for rapid, multi-sample structural variant visualization	compare sheet .bam files
Dose response	This Capsule produces dose response curves that describe the magnitude of the response as a function of exposure (dose) to a condition after a certain exposure time.	.csv file containing gene expression and treatment dosage (see README for details)
DESeq2	This Capsule performs differential gene expression analysis with potential input types: 1. Transcript abundance; 2. Counts data; 3. HTseq-counts data; 4. Summarized experiment in RDS format.	Input varies depending on the source (i.e., Seurat vs RSEM) see README for details.
Mol* Viewer for PDB Files	This Capsule allows you to view PDB files interactively on a Streamlit cloud workstation using the Mol* 3D Viewer.	Protein structure files in .pdb format
TensorBoard GPU	View model experiment metrics like loss and accuracy, visualizing the model graph, project embeddings to a lower dimensional space and more. This capsule shows an example from the Tensorboard website. This capsule runs on GPU instances and comes preloaded with Tensorflow.	None
RShiny Cell	ShinyCell is an R package that allows users to create interactive Shiny-based web applications to visualize single-cell data.	Single cell .rds inputs from Seurat (see README)
1-3. Single Cell Analysis Tutorial (Scanpy & Seurat)	Tutorials to describe working with Single Cell data for Scanpy and Seurat: 1. Preprocessing and clustering 3k PBMCs 2. Core Plotting Functions 3. How to preprocess UMI count data with analytic Pearson residuals	Tutorial datasets (see README for details)
5-6. Single Cell Analysis Tutorial (Scanpy)	Tutorials demonstrating how to regress cell cycle effect and how to simulate data using a literature-curated boolean gene regulatory network.	Tutorial datasets (see README for details)
7-10. Single Cell Analysis Tutorial (Scanpy) Advanced	Tutorials for advanced Single Cell processing.	Tutorial datasets (see README for details)

MLflow Orchestrator Capsule	This is a central MLflow "Orchestrator" capsule that can be used to interactively view the results from multiple machine learning capsules using the same MLflow database.	None

Title

Description

Input Data

Wally visualizations

This Capsule creates a genomic alignment plot of reads in a specified region mapped to a reference. The visualization of genomic alignments was heavily inspired by IGV, and customized to visualize structural variation and CNVs.

Genome .fasta reference and .fai file
.bam files

Samplot Visualization (from coordinates)

a command line tool for rapid, multi-sample structural variant visualization

compare sheet

.bam files

Dose response

This Capsule produces dose response curves that describe the magnitude of the response as a function of exposure (dose) to a condition after a certain exposure time.

.csv file containing gene expression and treatment dosage (see README for details)

DESeq2

This Capsule performs differential gene expression analysis with potential input types: 1. Transcript abundance; 2. Counts data; 3. HTseq-counts data; 4. Summarized experiment in RDS format.

Input varies depending on the source (i.e., Seurat vs RSEM) see README for details.

Mol* Viewer for PDB Files

This Capsule allows you to view PDB files interactively on a Streamlit cloud workstation using the Mol* 3D Viewer.

Protein structure files in .pdb format

TensorBoard GPU

View model experiment metrics like loss and accuracy, visualizing the model graph, project embeddings to a lower dimensional space and more. This capsule shows an example from the Tensorboard website.

This capsule runs on GPU instances and comes preloaded with Tensorflow.

None

RShiny Cell

ShinyCell is an R package that allows users to create interactive Shiny-based web applications to visualize single-cell data.

Single cell .rds inputs from Seurat (see README)

1-3. Single Cell Analysis Tutorial (Scanpy & Seurat)

Tutorials to describe working with Single Cell data for Scanpy and Seurat:

1. Preprocessing and clustering 3k PBMCs

2. Core Plotting Functions

3. How to preprocess UMI count data with analytic Pearson residuals

Tutorial datasets (see README for details)

5-6. Single Cell Analysis Tutorial (Scanpy)

Tutorials demonstrating how to regress cell cycle effect and how to simulate data using a literature-curated boolean gene regulatory network.

Tutorial datasets (see README for details)

7-10. Single Cell Analysis Tutorial (Scanpy) Advanced

Tutorials for advanced Single Cell processing.

Tutorial datasets (see README for details)

MLflow Orchestrator Capsule

This is a central MLflow "Orchestrator" capsule that can be used to interactively view the results from multiple machine learning capsules using the same MLflow database.

None

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