semvec/pypi-packages huggingface dataset:
supercells 0.0.5
Easily assess quality control data across multiple single cell datasets
Requires Python: >=3.7

![Supercells](https://user-images.githubusercontent.com/9028967/122049119-b81ece00-cdea-11eb-9f13-9f09e20eb537.png)
---


**Easily assess quality control data across multiple single cell datasets**

Supercells is a tool which generates a single report for multiple 10x cellranger samples - thus saving time and allowing comparative QC analysis.

It is written in Python (tested with v3.7-3.9).

[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg?style=flat-square)](https://github.com/ambv/black)
[![PyPI Version](https://img.shields.io/pypi/v/supercells.svg?style=flat-square)](https://pypi.python.org/pypi/supercells/)
[![Downloads](https://static.pepy.tech/badge/supercells)](https://pepy.tech/project/supercells)
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<br /> 




## 📦  Installation

Using PyPI:

`pip install supercells`

Clone or download the repository and navigate to the package directory, then invoke:

`pip install . `


## 💻  Usage

Once supercells is installed it is run by invoking:

`supercells -i <experiment folder>`

Unless specified otherwise it will generate `supercells_report.html` within the input folder as well as `supercells_report` folder containing summarizing xlsx file and CSV with the raw data. To specify an output directory use the ` -o <output folder>` flag

![image](https://user-images.githubusercontent.com/9028967/222570081-d8db435a-5683-4c0b-bc86-42c95b54c186.png)

### More options

```
usage: supercells [-h] [--version] --input INPATH [--output OUTPATH] [--cutoff-dict CUTOFF_DICT_PATH]

supercells: Easily assess quality control data across multiple single cell datasets

options:
  -h, --help            show this help message and exit
  --version, -v         show program's version number and exit
  --input INPATH, -i INPATH
                        Enter the location of the input files
  --output OUTPATH, -o OUTPATH
                        Specify the location of the output files, default is current wd
  --cutoff-dict CUTOFF_DICT_PATH, -c CUTOFF_DICT_PATH
```

`cutoff-dict` parameters is a file path to a json file. 
This is a sample of the json:
```json
{
    "Mean Reads per Cell": 20000,
    "Median Genes per Cell": 1500,
    "Valid Barcodes": "75%",
    "Sequencing Saturation": "30%",
    "Q30 Bases in RNA Read": 65,
    "Fraction Reads in Cells": "70%",
    "Reads Mapped to Genome": "75%",
    "Reads Mapped Confidently to Transcriptome": "30%"
}
```
The keys are the field names and the values are cutoff values for that field. i.e. **Mean Reads per Cell** cutoff  
value is **20000**. So for each sample if the **Mean Reads per Cell** is less than **20000** the output would show  
that cell in <span style="color:red">red</span>, else in <span style="color:green">green</span>.



## Further development
Suggestions for additional features and code contributions are welcomed
audible-series 1.1.0
Adds a command to audible-cli that looks for new series releases in a user's library.
Requires Python: <3.12,>=3.8
Keywords: audible

# Audible Series Command

## Installation

```
pip3 install audible
pip3 install audible-cli
pip3 install audible-series
```

## Usage

The command will work on an exported library file:

```
audible library export
audible series -l $PWD/library.csv -c $PWD/config.yaml
```

The config file is optional but can be used to override book data in cases where
a book is already preordered, a series should be ignored, or if audible data is
bad.  It can also be used to manually set a case where a book was read somewhere
else but it is not in your library (though this requires manually looking up the
audible ASIN).

## Development


This project uses poetry which wraps a bunch of tools like virtualenv.  The
easiest way to run it for development is to clone this repository then run a
poetry shell.

```
poetry shell
set -x AUDIBLE_PLUGIN_DIR $PWD/audible_series
audible library export
audible series -l $PWD/library.csv -c $PWD/config.yaml
```

When developing the `--only_series` flag may be useful since it will filter the
library to a single series.

## Publishing

```
poetry build
poetry publish
```

This will require an API token to pypi.  You can create one then configure poetry via: `poetry config pypi-token.pypi your-api-token`
diamond-hpc 0.0.8
Diamond is a Python package for running tasks on HPC.
Requires Python: >=3.8

# Diamond

## Tutorial

### Set up globus compute endpoint
Before we start, we need to create a globus compute endpoint in a HPC. Config samples can be find in `endpoint_configs`.
Run the following commands in target HPC to initialize the endpoint
```
pip install globus-compute-endpoint
globus-compute-endpoint configure {{ endpoint_name }} Diamond/endpoint_configs/{{ HPC }}/{{ config_file }}
globus-compute-endpoint start endpoint_name
```

### Run scripts in remote hpc via diamond

#### login
Run
```
diamond-hpc get-oauth2-url-and-login
```
This cli will return an oauth2 url and wait for the user input, open the url in your broswer and follow the authorization process, finally you will get a token.
Copy the token and input it back to the terminal, finish the authorization process

#### register container
1. create an container build endpoint by configure and start custom-image-builder-config.yaml in the globus endpoint server
2. run the following command(substitude the relevent text with your config)
```
diamond-hpc register-container --endpoint_id e099b614-c95e-4148-8ed9-6bd4684b92bc --work_path /work/09912/haotianxie/frontera --image_file_name 
openfold --base_image gcyang/openfold:0.1
```
This process may take a long time.

#### submit task via script file
1. create an container build endpoint by start endpoint in the globus endpoint server
2. run the following command(substitude the relevent text with your config)
```
diamond-hpc run-task-from-script --cmd_script /home/hotine/work/Diamond/example/sample_task/openfold_single_node_task --endpoint_id fb1ffeec-aa63-4136-8a49-f3f24608d36f --container_id a20b806c-29a8-44b4-97b6-591434ca9365 --log_path /work/09912/haotianxie/frontera/openfold_demo_single_node.log
```