semvec/pypi-packages huggingface dataset:
harlow 0.1.0
Adaptive surrogate modelling
Requires Python: >=3.7

# harlow

[![Docs](https://github.com/TNO/harlow/actions/workflows/build-docs.yml/badge.svg?branch=master)](https://tno.github.io/harlow/)
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Adaptive surrogate modelling.

`f_target(x) ~ f_surrogate(x)`

Harlow is an Adaptive Surrogate Modeling package, in Python.
The package offers a wide range of GPU-trainable Surrogate Models for single input-output and multi input-output pairs. Additionaly a series of Adaptive Samplers is implemented that work with multivariate data providing real-time web-logging. The package offers an intergration and benchmark test suite with numerous test functions and a real case study along with visualization functionality.

#### DISCLAIMER: This repository is in development. There's no guarantee in terms of code quality or output.

## On using the repository

* Install dependencies and the code from this repo:

```commandline
pip install -e .
```

* Install with additional dependencies for building documentation:

```commandline
pip install -e .[docs]
```

* To build the documentation locally:

```commandline
sphinx-build -b html docs/source docs/build
```

* To view the documentation open `docs/build/index.html`



* All code within this repository is expected to be run with the
    working directory set as the root directory of the repository.
cellenics-api 0.0.4
For programmatic upload of files to Cellencis
Requires Python: >=3.7

# cellenics-api

### About
This python package provides an easy way to create projects and upload samples into Cellenics.

### Installation
To install the package execute the following line:
`pip install cellenics_api`
 
### Usage
In order to use the package you first need to create an account in Cellenics (https://scp.biomage.net/) if you don't have one yet.

Then the package is used in the following way:
```python
import cellenics_api

# 1. Authenticate user and create a connection tunnel with the api
connection = cellenics_api.Connection('email', 'password')

# 2. Create an experiment
experiment_id = connection.create_experiment()

# 3. Upload samples associated with the experiment
connection.upload_samples(experiment_id, 'local/path/to/samples')
```
Once the upload is complete you can navigate to [Cellenics](https://scp.biomage.net/) and process your project there.

### Troubleshooting

`Max retries exceeded with url: / (Caused by SSLError(SSLEOFError(8, 'EOF occurred in violation of protocol (_ssl.c:2396)')))`
1. Navigate to your project in [Cellenics](https://scp.biomage.net/) and manually delete the failed sample
2. Run step #3 again

*This will be fixed when error handling is introduced*
tecount 1.0.1
Count read alignments on transposable elements subfamilies, families and classes.
Requires Python: >=3.7

![GitHub Workflow Status](https://img.shields.io/github/workflow/status/bodegalab/tecount/Upload%20Python%20Package?logo=github)
[![PyPI](https://img.shields.io/pypi/v/tecount?logo=python)](https://pypi.org/project/tecount/)
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# TEcount

A package to count reads mapping on transposable elements (TEs) subfamilies, families and classes in bulk RNA-seq.

## Features

TEcount counts high-throughput sequencing reads aligned on TEs on a reference genome.
It reports TE counts by subfamily, family and class on separate outputs.
In case of reads aligning on multiple TE loci, it counts only one alignment occurrence for each feature (i.e. subfamily, family or class).
It can use single or paired end BAM files, count in strand-specific manner and filter by a minimum read-TE overlap, among other features that can be discovered by running `TEcount --help`.

## Install

### Using conda  (recommended)
We recommend using conda, as it will install all the required packages along TEcount.
```bash
conda create -n tecount -c conda-forge -c bioconda tecount
```

### Using pip
If for any reason it's not possible or desiderable to use conda, it can be installed with pip and the following requirements must be installed manually: `python>=3.7`, `samtools>=1.14` and `bedtools>=2.30.0`.
```bash
pip install tecount
```

## Usage
Requires a BAM file sorted by coordinates and a bed6+3 file with subfamily, family and class in columns 7, 8 and 9.

```bash
TEcount -b <sorted_by_coord.bam> -r <rmsk.bed>
```

Example using test dataset:
```bash
TEcount -b ./test/Aligned.sortedByCoord.out.bam  -r ./test/rmsk.GRCm38.chr19.bed.gz
```

See all available parameters with:
```bash
TEcount --help
```

## Acknowledgements
Based on the transposable elements RNA-seq quantification strategy implemented in [1](#1).

## References
<a name="1"></a>1. Marasca, F., Sinha, S., Vadalà, R. et al. LINE1 are spliced in non-canonical transcript variants to regulate T cell quiescence and exhaustion. Nat Genet 54, 180–193 (2022). https://doi.org/10.1038/s41588-021-00989-7
pryeact 0.0.2.5
Package to componentize interface items created in QT Design.
Requires Python: >=3.8

pryeact
=============

#### Esse pacote python converte interfaces gráficas criadas no Qt designer para python usando o conceito de componente.

#### Exemplos


#### Requisitos
#### Pyqt5

#### Instalação

    `pip install pryeact`
    
#### Uso