PlutoBio 0.1.13

A Python SDK for Pluto.bio

Pluto Python SDK: py-pluto

A Python Software Development Kit (SDK) for interacting with the Pluto Bio, a cloud computational biology platform.

Other resources:

• Pluto.bio

• Pluto R Package.

• Pluto API

Table of Contents

• Installation
  • Using pip
  • Local Installation
• Configuration
• Usage
  • Initialize the Client
  • Experiment Operations
  • Sample and Assay Data
  • Plot Operations
  • Attachment Operations
• Examples
  • Uploading a plot to Pluto Experiment using plotly
  • Update an already existing plot in an experiment
  • List your experiments
  • List attachments in an experiment
  • Create and update external plots using simplified API
• Development
  • Build Distribution Package
  • Install from Source
• Help & Support

Installation

Using pip

To install the SDK using pip, run the following command:

pip install PyPluto

Local Installation

For a local setup, you can use a Python virtual environment.

python -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt

Configuration

Create an API key and set the environment variables to interact with the Pluto Bio platform. You can find your api token in the Pluto platform or visit this help article.

export PLUTO_API_URL=<API_URL>
export API_TOKEN=<API_TOKEN>

Usage

Initialize the Client

To start interacting with the Pluto Bio API, initialize the client with your API token.

from plutobio import PlutoClient

pluto_bio = PlutoClient(token="YOUR_PLUTO_API_TOKEN")

Experiment Operations

List Experiments

experiments = pluto_bio.list_experiments()

Get a Specific Experiment

experiment = pluto_bio.get_experiment("EXPERIMENT_UUID")

Sample and Assay Data

Get Sample Data

sample_data = pluto_bio.get_sample_data("EXPERIMENT_UUID", folder_path="data")

Get Assay Data

assay_data = pluto_bio.get_assay_data("EXPERIMENT_UUID", folder_path="data")

Plot Operations

List Plots

plots = pluto_bio.list_plots("EXPERIMENT_UUID")

Get Data from a Plot

plot_data = pluto_bio.get_plot_data("EXPERIMENT_UUID", "PLOT_UUID")

Create an External Plot

Create an external plot using the simplified API endpoint:

plot = pluto_bio.create_external_plot(
    experiment_id="EXPERIMENT_UUID",
    name="My External Plot",
    origin="python",
    methods="Optional methods description",
    results_file_id="OPTIONAL_RESULTS_FILE_UUID",
    display_file_id="OPTIONAL_DISPLAY_FILE_UUID",
    script_file_id="OPTIONAL_SCRIPT_FILE_UUID"
)

Update an External Plot

Update an existing external plot using the simplified API endpoint:

plot = pluto_bio.update_external_plot(
    experiment_id="EXPERIMENT_UUID",
    plot_uuid="PLOT_UUID",
    name="Updated Plot Name",
    origin="python",
    methods="Updated methods description",
    results_file_id="OPTIONAL_RESULTS_FILE_UUID",
    display_file_id="OPTIONAL_DISPLAY_FILE_UUID",
    script_file_id="OPTIONAL_SCRIPT_FILE_UUID"
)

Attachment Operations

List Attachments

attachments = pluto_bio.list_attachments("EXPERIMENT_UUID")

Download Attachments

attachment = pluto_bio.download_attachments("EXPERIMENT_UUID", "ATTACHMENT_UUID", folder_path="data")

Download QC report

qc_report = pluto_bio.download_qc_report("PLX128193", folder_path="data")

Download BAM files

bam_files = pluto_bio.download_bam_files("PLX128193", _bam_uuid, folder_path="data")

Note: File will show up locally in your machine in a folder called data in the same directory where you ran the script

Examples

Example : Uploading a plot to Pluto Experiment using plotly

import plotly.graph_objects as go
from plotly.offline import plot

# Let's say we have the following plot

fruits = ["Apples", "Bananas", "Cherries", "Dates"]
quantities = [
    10,
    20,
    15,
    7,
]


# Create a bar plot
fig = go.Figure(
    data=[
        go.Bar(
            x=fruits,
            y=quantities,
            marker_color="red"
        )
    ]
)

# Customize the layout
fig.update_layout(
    title="Fruit Quantities",
    xaxis=dict(title="Fruit"),
    yaxis=dict(title="Quantity"),
    paper_bgcolor="rgba(0,0,0,0)",
    plot_bgcolor="rgba(0,0,0,0)",
)

plot(fig, filename="bar_plot.html", auto_open=False)

pc.create_or_update_plot(
    _experiment_uuid,
    file_path="bar_plot.html",
)

Example : Update an already existing plot in an experiment

To update an existing plot in your experiment, you will need the figure uuid. To find out the uuid click on the 3 dots in the figure, and select the option methods. The uuid that you want is under plot analysis ID.

import plotly.graph_objects as go
from plotly.offline import plot

# Let's say we have the following plot

fruits = ["Apples", "Bananas", "Cherries", "Dates"]
quantities = [
    10,
    20,
    15,
    7,
]


# Create a bar plot
fig = go.Figure(
    data=[
        go.Bar(
            x=fruits,
            y=quantities,
            marker_color="red"
        )
    ]
)

# Customize the layout
fig.update_layout(
    title="Fruit Quantities",
    xaxis=dict(title="Fruit"),
    yaxis=dict(title="Quantity"),
    paper_bgcolor="rgba(0,0,0,0)",
    plot_bgcolor="rgba(0,0,0,0)",
)

plot(fig, filename="bar_plot.html", auto_open=False)

pc.create_or_update_plot(
    _experiment_uuid,
    file_path="bar_plot.html",
    plot_uuid=<PLOT_UUID>  # example "6511b617-9a0e-4a61-bf30-a1f1eea7a2a4",
)

Example : List your experiments

from plutobio import PlutoClient
pluto_bio = PlutoClient(token="YOUR_PLUTO_API_TOKEN")

experiments = pluto_bio.list_experiments()

experiments = pluto_bio.list_experiments()
for experiment in experiments:
    print(f"Pluto ID: {experiment} | Name: {experiments[experiment].name}")


>>>> Pluto ID: PLX128193 | Name: Novel therapeutics inhibiting viral replication in SARS-CoV-2
>>>> Pluto ID: PLX122909 | Name: testing
>>>> Pluto ID: PLX004016 | Name: test-analysis-btn
>>>> Pluto ID: PLX176024 | Name: New test title
>>>> Pluto ID: PLX175808 | Name: Testing banners
>>>> Pluto ID: PLX169820 | Name: Iowa Test - Copy of Copy of PLX160374: Cut and Run TM ET H3K16Ac
>>>> Pluto ID: PLX174997 | Name: Copy of Iowa Test - Copy of Copy of PLX160374: Cut and Run TM ET H3K16Acdaf

Example : List attachments in an experiment

from plutobio import PlutoClient
pluto_bio = PlutoClient(token="YOUR_PLUTO_API_TOKEN")

attachments = pluto_bio.list_attachments("PLX128193")
for attachment in attachments:
    print(f"Filename: {attachment.filename} | UUID: {attachment.uuid}")

>>>> Filename: SRR4238351_subsamp.fastq.gz | UUID: 634cd346-4674-4f3c-97ea-d17cf146453b

Example : Create and update external plots using simplified API

from plutobio import PlutoClient
pluto_bio = PlutoClient(token="YOUR_PLUTO_API_TOKEN")

# Create a new external plot
new_plot = pluto_bio.create_external_plot(
    experiment_id="EXPERIMENT_UUID",
    name="My External Plot",
    origin="python",
    methods="This plot shows the relationship between variables X and Y",
    results_file_id="OPTIONAL_RESULTS_FILE_UUID",  # Optional
    display_file_id="OPTIONAL_DISPLAY_FILE_UUID",  # Optional
    script_file_id="OPTIONAL_SCRIPT_FILE_UUID"     # Optional
)

print(f"Created new plot with UUID: {new_plot.uuid}")

# Update an existing external plot
updated_plot = pluto_bio.update_external_plot(
    experiment_id="EXPERIMENT_UUID",
    plot_uuid=new_plot.uuid,
    name="Updated Plot Name",
    methods="Updated methods description with more details",
    # Optional fields:
    # results_file_id="UPDATED_RESULTS_FILE_UUID",
    # display_file_id="UPDATED_DISPLAY_FILE_UUID",
    # script_file_id="UPDATED_SCRIPT_FILE_UUID"
    # Note: You can update only the fields you want to change
)

print(f"Updated plot: {updated_plot.name}")

---

Development

Build Distribution Package

To build a distribution package, navigate to the project's root directory and run:

python setup.py sdist bdist_wheel

Install from Source

It's recommended to use a virtual environment to install the Pluto SDK package from source.

python -m venv .venv
source .venv/bin/activate
pip install git+ssh://github.com/pluto-biosciences/py-pluto.git@VERSION_TAG

Help and Support

For additional assistance please visit our knowledge base or submit a support request via the help portal.