semvec/pypi-packages huggingface dataset:
methQC 0.2.3
Quality Control (QC), Visualization/plotting, and postprocessing software for Illumina methylation array data. See https://life-epigenetics-methqc.readthedocs-hosted.com/en/latest/ for full documentation and examples.
License: MIT
Keywords: methylation dna data processing epigenetics illumina

# methQC
methQC is a Python-based package for filtering and visualizing Illumina methylation array data. The focus is on quality control.

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# MethQC Package

MethQC is designed to accept the output from the MethPype package.

It contains both high-level APIs for processing data from local files and low-level functionality allowing you to customize the flow of data and how it is processed.

# Installation

This package is available in PyPi.
`pip install methQC`

# How to use it

In general, the best way to import data is to use `methpype` and run `run_pipeline(data_folder, betas=True)`, collect the beta_values.pkl file it returns/saves to disk, and load that in a Jupyter notebook with methQC. From there, each data transformation is a single line of code using Panadas DataFrames. `methQC` will keep track of the data format/structures for you, and you can visualize the effect of each filter as you go. You can also export images of your charts for publication.

Refer to the Jupyter notebooks on readthedocs for examples of filtering probes from a batch of samples, removing outlier samples, and generating plots of data.

# Authors

Parts of this package were ported from `minfi`, a `R` package, and extended/developed by the team at Life Epigenetics, who maintains it. You can write to `info@LifeEgx.com` to give feedback, ask for help, or suggest improvements. For bugs, report issues on our github repo page.
konfi 0.2.1
Python config management, but cute.
License: MIT

# konfi

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konfi lets you create config templates similar to 
[dataclasses](https://docs.python.org/3/library/dataclasses.html). 
These templates are then used to load the config from different sources.
konfi guarantees that the loaded config corresponds to the template even
going as far as making sure items of a list are of the right type.

This means you no longer have to worry about the validity of the config,
if the config is correct it will load and if it isn't it will raise an
error telling you why not.


## Installation

You can install konfi from [PyPI](https://pypi.org/project/konfi/):

```bash
pip install konfi
```


## Example

```python
from typing import Optional

import konfi


@konfi.template()
class UserInfo:
    name: str
    country: Optional[str]


@konfi.template()
class AppConfig:
    name: str = "konfi"
    user: UserInfo


konfi.set_sources(
    konfi.YAML("config.yml", ignore_not_found=True),
    konfi.Env(prefix="app_"),
)

config = konfi.load(AppConfig)

greeting = f"Hello {config.user.name}"
if config.user.country:
    greeting += f" from {config.user.country}"

print(greeting)
print(f"Welcome to {config.name}!")
```

For more examples see the [examples/](examples) directory.


## Documentation

If you're ready to jump in, you can find the documentation on 
[Read the Docs](https://konfi.giesela.dev).