Getting Started with OpenNano

Welcome to OpenNano! This guide will help you get started with installing and using the OpenNano package for analyzing NanoString GeoMx data.

Installation

To install OpenNano, use pip:

pip install opennano

Alternatively, you can clone the repository and install it locally:

git clone https://github.com/your-username/opennano.git
cd opennano
pip install .

Requirements

Ensure you have the following dependencies installed:

  • Python 3.8+

  • pandas

  • anndata

  • numpy

  • scipy

  • matplotlib

  • seaborn

  • scikit-learn

  • scanpy

Basic Usage

The OpenNano package provides a seamless way to process NanoString GeoMx data and perform quality control (QC). Below is a quick walkthrough of the main features.

### Processing GeoMx Data

Use the GeoMxProcessor class to parse .dcc, .pkc, and GEO SOFT metadata files and create an AnnData object for downstream analysis.

from opennano.io import GeoMxProcessor

processor = GeoMxProcessor(
    dcc_files="path/to/dcc_directory",
    pkc_file="path/to/probes.pkc",
    metadata_file="path/to/metadata.txt"
)

adata = processor.process()
print(adata)
# Output: AnnData object with n_obs x n_vars = <features> x <samples>

### Performing QC Checks

The CountsQC class allows you to perform quality control on the AnnData object.

from opennano.qc import CountsQC

qc = CountsQC(adata=adata)

# Plot QC metrics
qc.plot_qc_results()

# Run all QC checks
filtered_adata = qc.run_all_checks()
print(filtered_adata)

Advanced Features

  • Independent File Parsing:

    You can parse .dcc, .pkc, and GEO SOFT metadata files separately using static methods like read_dcc_file, read_pkc, and parse_geo_soft_metadata_with_identifier in the GeoMxProcessor class.

    from opennano.io import GeoMxProcessor

dcc_data = GeoMxProcessor.read_dcc_file("sample1.dcc")
print(dcc_data["Code_Summary"])
  • Custom QC Thresholds:

    Adjust QC thresholds directly when creating a CountsQC object:

    qc = CountsQC(
    adata=adata,
    minSegmentReads=500,
    percentTrimmed=85,
    percentAligned=80
)

filtered_adata = qc.run_all_checks()

Visualization

OpenNano provides rich visualization options for inspecting QC metrics and comparing data before and after filtering. Here is an example:

qc.plot_before_after_filtering()

Contributing

Contributions are welcome! Please visit our GitHub repository to report issues or submit pull requests:

GitHub Repository

Support

If you have any questions or need help, please check the documentation or contact the maintainers through GitHub Discussions.

Happy analyzing with OpenNano!