semvec/pypi-packages huggingface dataset:
BLADE-Deconvolution-anoyaro 0.0.1
BLADE (Bayesian Log-normAl DEconvolution)
Requires Python: >=3.6

<p align="center">
  <img width="231" height="271.5" src="https://github.com/tgac-vumc/BLADE/blob/master/logo_final_small.png">
</p>

# BLADE: Bayesian Log-normAl DEconvolution


BLADE (Bayesian Log-normAl DEconvolution) was designed to jointly estimate cell type composition and gene expression profiles per cell type in a single-step while accounting for the observed gene expression variability in single-cell RNA-seq data. 

Demo notebook is available [here](https://github.com/tgac-vumc/BLADE/blob/master/jupyter/BLADE%20-%20Demo%20script.ipynb).

<p align="center">
  <img width="490" height="820" src="https://github.com/tgac-vumc/BLADE/blob/master/framework.png">
</p>


## Installation

### Using Conda
### Step 1: Installing Miniconda 3
First, please open a terminal or make sure you are logged into your Linux VM. Assuming that you have a 64-bit system, on Linux, download and install Miniconda 3 with:

```
wget https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh
bash Miniconda3-latest-Linux-x86_64.sh
```
On MacOS X, download and install with:

```
curl https://repo.continuum.io/miniconda/Miniconda3-latest-MacOSX-x86_64.sh -o Miniconda3-latest-MacOSX-x86_64.sh
bash Miniconda3-latest-MacOSX-x86_64.sh
```

### Step 2: Create a conda environment

You can install all the necessary dependency using the following command.

```
conda install mamba -c conda-forge -y
mamba create --name BLADE -c conda-forge -c bioconda jupyter numpy numba scikit-learn joblib multiprocess time scipy qgrid seaborn
```

Then, the `BLADE` environment can be activate by:

```
conda activate BLADE
```

### Using Singularity

If you have Singularity, you can simply pull the singularity container with all dependency resolved.

```
singularity pull shub://tgac-vumc/BLADE
```
yaml-include 1.0.0
Tool to generate yaml file with include
Requires Python: >=3.4

# yaml-include

## Install
Simply install this tool using pip :

`pip install yaml-include`

## Features :

* Include document using `!include <PATH>`
* Recursive inclusion
* Relative & absolute path

## Usage

Given those three files :

**root.yaml**
```yaml
- Document :
    !include version.yaml

- Job :
    !include jobs/job1.yaml
```

**version.yaml**
```yaml
- name : "4.19.35"
- sha1 : "37dadf3"
```

**jobs/job1.yaml**
```yaml
- name: "Test"
- target: "imx8mq"
```

You can generate your file with included documents using :

`yaml-include root.yaml --output-file generated.yaml`

or simply print the result :

`yaml-include root.yaml`

Resulting this output :

```yaml
- Document:
  - name: 4.19.35
  - sha1: 37dadf3
- Job:
  - name: Test
  - target: imx8mq

```

### Help

```
usage: yaml-include [-h] [-o OUTPUT_FILE] root_document

positional arguments:
  root_document         Root document

optional arguments:
  -h, --help            show this help message and exit
  -o OUTPUT_FILE, --output-file OUTPUT_FILE
                        Path for your generated file.
```
BLADE-anoyaro 0.0.1
BLADE (Bayesian Log-normAl DEconvolution)
Requires Python: >=3.6

<p align="center">
  <img width="231" height="271.5" src="https://github.com/tgac-vumc/BLADE/blob/master/logo_final_small.png">
</p>

# BLADE: Bayesian Log-normAl DEconvolution


BLADE (Bayesian Log-normAl DEconvolution) was designed to jointly estimate cell type composition and gene expression profiles per cell type in a single-step while accounting for the observed gene expression variability in single-cell RNA-seq data. 

Demo notebook is available [here](https://github.com/tgac-vumc/BLADE/blob/master/jupyter/BLADE%20-%20Demo%20script.ipynb).

<p align="center">
  <img width="490" height="820" src="https://github.com/tgac-vumc/BLADE/blob/master/framework.png">
</p>


## Installation

### Using Conda
### Step 1: Installing Miniconda 3
First, please open a terminal or make sure you are logged into your Linux VM. Assuming that you have a 64-bit system, on Linux, download and install Miniconda 3 with:

```
wget https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh
bash Miniconda3-latest-Linux-x86_64.sh
```
On MacOS X, download and install with:

```
curl https://repo.continuum.io/miniconda/Miniconda3-latest-MacOSX-x86_64.sh -o Miniconda3-latest-MacOSX-x86_64.sh
bash Miniconda3-latest-MacOSX-x86_64.sh
```

### Step 2: Create a conda environment

You can install all the necessary dependency using the following command.

```
conda install mamba -c conda-forge -y
mamba create --name BLADE -c conda-forge -c bioconda jupyter numpy numba scikit-learn joblib multiprocess time scipy qgrid seaborn
```

Then, the `BLADE` environment can be activate by:

```
conda activate BLADE
```

### Using Singularity

If you have Singularity, you can simply pull the singularity container with all dependency resolved.

```
singularity pull shub://tgac-vumc/BLADE
```
Pandas2Shp 0.0.2
Create shp file for geo-spatial analysis from longitude and latitude

What is it?
===========

Pandas2Shp module create shape file using latitude and longitude information from pandas columns or python list. Shape file are needed for geo-spatial data analysis.

Input parameters
================

  - **longitude** Pandas series or dataframe column or numpy array or python list.
  - **latitude** Pandas series or dataframe column or numpy array or python list.
  - **output_path** Directory where you want to save the shape file.
  - **file_name** File name to be kept for shape file in the given output path.

How to use is it?
=================

```python

from Pandas2Shp import Pandas2Shp

long=[-14.394,-9.03,-25.171,-6.712000000000001,-7.932,-8.445,-8.47,-9.355,-7.48,-7.888999999999999,-31.131,-7.966,-28.03,-28.715999999999998,-27.093000000000004,-8.887,-9.036,-25.698,-28.44,-8.584]
lat=[-7.968999999999999,38.883,36.971,41.868,38.079,41.586999999999996,40.157,38.725,40.265,38.533,39.455,37.014,39.092,38.52,38.764,39.830999999999996,38.704,37.741,38.554,37.149]
output_path='/home/user/airport/'
file_name='airports'

myObj=Pandas2Shp(longitude,latitude,output_path,file_name)
myObj.getShp()

```

Where to get it?
================

`pip install Pandas2Shp`

Dependencies
============

 - [geopandas](https://geopandas.org/)
 - [pandas](https://pandas.pydata.org/)
dateutils 0.6.12
Various utilities for working with date and datetime objects

dateutils
=========

The main purpose of this package is to provide more complex arithmetic
operations on dates/times. Heavy use is made of the relativedelta type from
Labix's dateutil library. Much of this package is just a light wrapper on top
of this with some added features such as range generation and business day
calculation.

Installation
------------

You should install dateutils with pip:

    pip install dateutils

Otherwise, you'll have to download the package and run:

    python setup.py install

If you install it this way then you will also have to install all necessary
dependencies manually.