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Streamlit Python Docker PerSeqPipe

⭐ Introduction

PerSeqPIPE VIZ is a user-friendly application for visualizing results from the PerSeqPIPE pipeline, built using the Streamlit library.

Current version of PerSeqPIPE VIZ has 4 sections, each specializing in interactive exploration and visualization of specific data produced by PerSeqPIPE:

  1. Reads Counts Viewer: Exploration and visualization of read statistics after each step of preprocessing in the PerSeqPIPE workflow
  2. sncRNA Counts Viewer: Exploration of sequence-centric results from PerSeqPIPE workflow
  3. DE Analysis Viewer: Visualization of results from differential dxpression (DE) analysis, including PCA plot and interactive heatmaps
  4. Reads Coordinate Extraction: Extract information about specific read sequences, such as coordinates for visualization in the IGV tool, mismatches, strand etc.

For more information about each section, see the Sections documentation.

💻 Usage

🐳 Quick start (using Docker)

We provide a publicly available Docker image with all dependencies already installed. To run PerSeqPIPE VIZ using docker, execute the following code:

# For linux/amd64 infrastructure
docker pull ktrachtok/perseqpipe_viz:amd64-1.0.0
docker run -p 8502:8502 ktrachtok/perseqpipe_viz:amd64-1.0.0

# For arm infrastructure
docker pull ktrachtok/perseqpipe_viz:arm64-1.0.0
docker run -p 8502:8502 ktrachtok/perseqpipe_viz:arm64-1.0.0

This will start PerSeqPIPE VIZ at http://0.0.0.0:8502. When running through Docker, the web browser will not open automatically and must be started by the user. The application will be available after the following message appears in the terminal:

You can now view your Streamlit app in your browser.

URL: http://0.0.0.0:8502

The port 8502 can be changed to any available port using the PORT environment variable.

docker run -e PORT=8501 -p 8501:8501 ktrachtok/perseqpipe_viz:arm64-1.0

🔷 Quick start (local installation)

Alternatively, PerSeqPIPE VIZ can also be run locally (without Docker).

First, download the repository code locally.

git clone https://github.com/ktrachtova/perseqpipe_viz.git

Next, install prerequisities stated in requirements using pip. Finally, run the following command:

streamlit run app.py

This will automnatically open the application in a your default web browser.

📥 Inputs

Inputs for the PerSeqPIPE VIZ are various files produced by the PerSeqPIPE workflow. Here is the overview of which files are required for which section of the PerSeqPIPE VIZ application.

Tab Input file(s)
Reads Counts Viewer read_counts_summary.csv
sncRNA Counts Viewer {sample}.genome.short_rna_counts.tsv
DE Analysis Viewer DE_analysis_[isomirs|mirna|sncrna]_results.tsv, DE_analysis_[isomirs|mirna|sncrna]_counts.tsv
Reads Coordinate Extraction {sample}.genome.Aligned.sortedByCoord.out.bam

For description of each input file and its location withing PerSeqPIPE results, please got to PerSeqPIPE VIZ Sections.

Providing inputs from different tools

As long as an input file for a specific section of PerSeqPIPE VIZ follows required format (columns, data types, etc.), then PerSePIPE VIZ will be able to work with it. If you want to visualize data obtained elsewhere, we recommend to inspect example inputs we provide and copy their format (column names, separators etc.).

🔆 System requirements

PerSeqPIPE VIZ does not require any special hardware or system resources beyond a standard modern computer. The application can run on typical desktop or laptop environments (macOS, or Linux) with Docker or Python installed, depending on the chosen setup method.

🎺 Credits

PerSeqPIPE VIZ application is written and maintaned by Karolina Trachtova (karolina.trachtova@ceitec.muni.cz).

⁉️ Support

In case of question, bugs or suggestions for improvement please open new issue here.

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Streamlit-based visualization application of PerSeqPIPE results.

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