pinpoint-sig 0.1.2

Personalized Integrated Nanopore Profiling of Individual (Copy-)Number Trajectories

PINPOINT

Personalized Integrated Nanopore Profiling Of Individual (Copy-)Number Trajectories

A Python tool for personalized cancer monitoring from pediatric CSF liquid biopsies, based on nanopore sequencing → ichorCNA → personalized CNA signal tracking over time.

---

What it does

• Finds a patient-specific CNA fingerprint from a reference tumor sample
• Tracks this signal longitudinally across follow-up CSF samples
• Scores each sample using a sign concordance score against the reference
• Visualizes results as temporal graphs and per-chromosome heatmaps
• Highlights suspected driver genes (COSMIC Cancer Gene Census) in altered regions

Installation

pip install pinpoint-sig

Or from source:

git clone https://github.com/nir-lavi/pinpoint.git
cd pinpoint
pip install -e .

Quick Start

import pinpoint
import datetime

# Add samples for a patient (first sample becomes reference automatically)
pinpoint.add_sample(
    patient        = "Patient_1",
    sample_name    = "CSF-001",
    sample_date    = datetime.datetime(2023, 1, 15),
    ichor_location = "/path/to/ichorCNA/CSF-001/",
    tumor_fraction = 0.42,
    coverage       = 1.8,
    disease_status = "AD",
    diagnosis      = "Medulloblastoma",
)

pinpoint.add_sample(
    patient        = "Patient_1",
    sample_name    = "CSF-002",
    sample_date    = datetime.datetime(2023, 4, 10),
    ichor_location = "/path/to/ichorCNA/CSF-002/",
    tumor_fraction = 0.05,
    coverage       = 0.5,
    disease_status = "NED",
    diagnosis      = "Medulloblastoma",
)

# Plot
pinpoint.plot_temporal("Patient_1", save=True)
pinpoint.plot_heatmap("Patient_1", genes=True, save=True)

Tutorial

A full worked example using a pediatric Pinealoblastoma case (9 longitudinal CSF samples over 17 months) is available in tutorial/PINPOINT_tutorial.ipynb.

The notebook covers:

• Adding samples and setting up a patient directory
• How the reference tumor fingerprint is selected
• Interpreting the signf score
• Generating and reading the temporal plot and heatmap

Note: The tutorial notebook is provided without raw data for patient privacy reasons.
To run it, point ICHOR_BASE to your own ichorCNA output directory.

Example Output

Temporal Score Trajectory

Longitudinal signf scores across 9 CSF samples. The patient transitions from Active Disease (red) to No Evidence of Disease (green), with scores dropping below the 0.2 threshold in remission.

Per-Chromosome Heatmap with Suspected Driver Genes

Per-chromosome sign concordance scores across all samples. Red columns indicate chromosomes with strong tumor signal. The gene panel below highlights COSMIC driver genes in altered regions — red = amplified oncogenes, blue = deleted tumor suppressors.

Input Requirements

Each sample requires ichorCNA output files in ichor_location/:

• {sample_name}.correctedDepth.txt
• {sample_name}.seg

Patient Directory Structure

Patient_1/
    info.tsv          # sample metadata + scores (auto-generated)
    reference.tsv     # reference CNA profile with informative mask
    plots/            # saved figures

API Reference

Function	Description
add_sample(patient, sample_name, ...)	Add a sample and compute scores
set_reference(patient, sample_name)	Change the reference sample
plot_temporal(patient, save=True)	Plot score + coverage timeline
plot_heatmap(patient, genes=True, save=True)	Plot per-chromosome heatmap

Citation

If you use PINPOINT in your research, please cite: (coming soon)

License

MIT