SciKits

Quick search

scikit-ribo

version 0.2.1b5

A scikit framework for joint analysis of Riboseq and RNAseq data

Download: https://pypi.python.org/pypi/scikit-ribo
Homepage: https://github.com/hanfang/scikit-ribo
PyPI: http://pypi.python.org/pypi/scikit-ribo
People: Han Fang

Description

![logo](logo.png)

# *scikit-ribo*

### - A scikit framework for joint analysis of Riboseq and RNAseq data
--------

## Contact

Han Fang
hanfang.cshl@gmail.com

## Requirement:
Environment: Python3, Linux

Dependencies:
bedtools >= 2.26.0

When using `pip install scikit-ribo`, all the following dependencies will be pulled and installed automatically.

| Python package| Version >= |
| ------------- |:-------------:|
| conda | 4.2.13 |
| colorama | 0.3.7 |
| glmnet-py | 0.1.0b |
| gffutils | 0.8.7.1 |
| matplotlib | 1.5.1 |
| numpy | 1.11.2 |
| pandas | 0.19.2 |
| pybedtools | 0.7.8 |
| pyfiglet | 0.7.5 |
| pysam | 0.9.1.4 |
| scikit-learn | 0.18 |
| scipy | 0.18.1 |
| seaborn | 0.7.0 |
| termcolor | 1.1.0 |

## Install

Install `scikit-ribo`

pip install scikit-ribo

## How-to-use

Twp steps:

- Build index: `scikit-ribo-build.py`

- Fit model: `scikit-ribo-run.py`

## Usage

1. Build index: `scikit-ribo-build.py`


```
scikit-ribo-build.py -g gtf-file -f fasta-file -p prefix -r rna-fold-folder -t TPM-file -o index-path

required arguments:
-g G Gtf file, required
-f F Fasta file, required
-p P Prefix to use, required
-r R Rnafold folder, required
-t T TPM of RNAseq sample, required
-o O Output path of the built indexes, required
```


2. Fit model: `scikit-ribo-run.py`

```
scikit-ribo-run.py -i bam-file -f index-path -p prefix -o output-path

required arguments:
-i I Input bam file
-f F path to the Folder of BED/index files generated by the pre-processing module
-p P Prefix for BED/index files
-o O Output path, recommend using the sample id

optional arguments:
-h, --help show this help message and exit
-q Q minimum mapQ allowed, Default: 20
-s S Shortest read length allowed, Default: 10
-l L Longest read length allowed, Default: 35
-c enable cross validation for glmnet
-r setting this flag will enable the RelE mode
-u U Un-mappable regions
```

## Introduction

## Reference

Preprint coming up


Installation

PyPI

You can download the latest distribution from PyPI here: http://pypi.python.org/pypi/scikit-ribo

Using pip

You can install scikit-ribo for yourself from the terminal by running:

pip install --user scikit-ribo

If you want to install it for all users on your machine, do:

pip install scikit-ribo
On Linux, do sudo pip install scikit-ribo.

If you don't yet have the pip tool, you can get it following these instructions.

This package was discovered in PyPI.