bccb Alternatives - Python Science and Data Analysis

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Description

Collection of useful code related to biological analysis. Much of this is discussed with examples at Blue collar bioinformatics.

Some projects which may be especially interesting:

Code Quality Rank: L4

Programming language: Python

Tags: Science And Data Analysis

Latest version: v0.6.5

bccb alternatives and similar packages

Based on the "Science and Data Analysis" category

Pandas

9.8 9.9 L2 bccb VS Pandas

A library providing high-performance, easy-to-use data structures and data analysis tools.
NumPy

9.6 9.8 L1 bccb VS NumPy

A fundamental package for scientific computing with Python.
SciPy

9.4 9.8 L2 bccb VS SciPy

A Python-based ecosystem of open-source software for mathematics, science, and engineering.
SymPy

9.3 10.0 L2 bccb VS SymPy

A Python library for symbolic mathematics.
NetworkX

9.2 8.6 L3 bccb VS NetworkX

A high-productivity software for complex networks.
statsmodels

9.0 9.6 L3 bccb VS statsmodels

Statistical modeling and econometrics in Python.
PyMC

8.7 9.2 L4 bccb VS PyMC

Markov Chain Monte Carlo sampling toolkit.
Numba

8.5 9.9 L3 bccb VS Numba

Python JIT (just in time) compiler to LLVM aimed at scientific Python by the developers of Cython and NumPy.
Dask

8.5 9.5 L2 bccb VS Dask

Versatile parallel programming with task scheduling
astropy

8.0 9.8 L2 bccb VS astropy

A community Python library for Astronomy.
Biopython

7.8 9.6 L2 bccb VS Biopython

Biopython is a set of freely available tools for biological computation.
blaze

7.8 2.1 L4 bccb VS blaze

NumPy and Pandas interface to Big Data.
orange

7.4 9.7 L2 bccb VS orange

Data mining, data visualization, analysis and machine learning through visual programming or Python scripting.
Interactive Parallel Computing with IPython

7.1 5.9 L3 bccb VS Interactive Parallel Computing with IPython

Interactive Parallel Computing in Python
Cubes

6.1 3.4 L3 bccb VS Cubes

Light-weight Python OLAP framework for multi-dimensional data analysis
Open Mining

5.8 0.0 L3 bccb VS Open Mining

Business Intelligence (BI) in Python (Pandas web interface)
RDKit

5.7 9.1 L1 bccb VS RDKit

Cheminformatics and Machine Learning Software.
bcbio-nextgen

5.5 9.3 L3 bccb VS bcbio-nextgen

A toolkit providing best-practice pipelines for fully automated high throughput sequencing analysis.
NIPY

5.1 9.2 L3 bccb VS NIPY

A collection of neuroimaging toolkits.
bcolz

4.7 4.0 bccb VS bcolz

A columnar data container that can be compressed.
Neupy

4.4 7.1 L5 bccb VS Neupy

Running and testing different Artificial Neural Networks algorithms.
Bubbles

3.6 0.0 L5 bccb VS Bubbles

A Python ETL framework
PyDy

2.9 6.0 L3 bccb VS PyDy

Short for Python Dynamics, used to assist with workflow in the modeling of dynamic motion based around NumPy, SciPy, IPython, and matplotlib.
harold

1.7 7.8 L2 bccb VS harold

An MIT licensed systems and controls toolbox for Python.
signac

1.0 8.5 bccb VS signac

Manage large and heterogeneous data spaces on the file system.
cclib

0.9 2.1 bccb VS cclib

A library for parsing and interpreting the results of computational chemistry packages.
dask-memusage

0.5 3.2 bccb VS dask-memusage

A low-impact profiler to figure out how much memory each task in Dask is using
Open Babel

- - bccb VS Open Babel

A chemical toolbox designed to speak the many languages of chemical data.

* Code Quality Rankings and insights are calculated and provided by Lumnify.
They vary from L1 to L5 with "L5" being the highest. Visit our partner's website for more details.

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README

Collection of useful code related to biological analysis. Much of this is discussed with examples at Blue collar bioinformatics.

All code, images and documents in this repository are freely available for all uses. Code is available under the MIT license and images, documentations and talks under the Creative Commons No Rights Reserved (CC0) license.

Some projects which may be especially interesting:

CloudBioLinux -- An automated environment to install useful biological software and libraries. This is used to bootstrap blank machines, such as those you'd find on Cloud providers like Amazon, to ready to go analysis workstations. See the CloudBioLinux effort for more details. This project moved to its own repository at https://github.com/chapmanb/cloudbiolinux.
gff -- A GFF parsing library in Python, aimed for inclusion into Biopython.
nextgen -- A python toolkit providing best-practice pipelines for fully automated high throughput sequencing analysis. This project has moved into its own repository: https://github.com/chapmanb/bcbio-nextgen
distblast -- A distributed BLAST analysis running for identifying best hits in a wide variety of organisms for downstream phylogenetic analyses. The code is generalized to run on local multi-processor and distributed Hadoop clusters.

*Note that all licence references and agreements mentioned in the bccb README section above are relevant to that project's source code only.