All Projects → marcelm → Cutadapt

marcelm / Cutadapt

Licence: mit
Cutadapt removes adapter sequences from sequencing reads

Programming Languages

python
139335 projects - #7 most used programming language

Projects that are alternatives of or similar to Cutadapt

Pygeno
Personalized Genomics and Proteomics. Main diet: Ensembl, side dishes: SNPs
Stars: ✭ 261 (-23.24%)
Mutual labels:  bioinformatics
Tdc
Therapeutics Data Commons: Machine Learning Datasets and Tasks for Therapeutics
Stars: ✭ 291 (-14.41%)
Mutual labels:  bioinformatics
Dash Cytoscape
Interactive network visualization in Python and Dash, powered by Cytoscape.js
Stars: ✭ 309 (-9.12%)
Mutual labels:  bioinformatics
Cobrapy
COBRApy is a package for constraint-based modeling of metabolic networks.
Stars: ✭ 267 (-21.47%)
Mutual labels:  bioinformatics
Dada2
Accurate sample inference from amplicon data with single nucleotide resolution
Stars: ✭ 276 (-18.82%)
Mutual labels:  bioinformatics
Edlib
Lightweight, super fast C/C++ (& Python) library for sequence alignment using edit (Levenshtein) distance.
Stars: ✭ 298 (-12.35%)
Mutual labels:  bioinformatics
Vcfanno
annotate a VCF with other VCFs/BEDs/tabixed files
Stars: ✭ 259 (-23.82%)
Mutual labels:  bioinformatics
Biopandas
Working with molecular structures in pandas DataFrames
Stars: ✭ 329 (-3.24%)
Mutual labels:  bioinformatics
Cdk
The Chemistry Development Kit
Stars: ✭ 283 (-16.76%)
Mutual labels:  bioinformatics
Bioinformatics One Liners
Bioinformatics one liners from Ming Tang
Stars: ✭ 309 (-9.12%)
Mutual labels:  bioinformatics
Manta
Structural variant and indel caller for mapped sequencing data
Stars: ✭ 271 (-20.29%)
Mutual labels:  bioinformatics
Arvados
An open source platform for managing and analyzing biomedical big data
Stars: ✭ 274 (-19.41%)
Mutual labels:  bioinformatics
Gwa tutorial
A comprehensive tutorial about GWAS and PRS
Stars: ✭ 303 (-10.88%)
Mutual labels:  bioinformatics
Seq
A high-performance, Pythonic language for bioinformatics
Stars: ✭ 263 (-22.65%)
Mutual labels:  bioinformatics
Jvarkit
Java utilities for Bioinformatics
Stars: ✭ 313 (-7.94%)
Mutual labels:  bioinformatics
Postgui
A React web application to query and share any PostgreSQL database.
Stars: ✭ 260 (-23.53%)
Mutual labels:  bioinformatics
Bionode
Modular and universal bioinformatics
Stars: ✭ 294 (-13.53%)
Mutual labels:  bioinformatics
Grakel
A scikit-learn compatible library for graph kernels
Stars: ✭ 330 (-2.94%)
Mutual labels:  bioinformatics
Dash Bio
Open-source bioinformatics components for Dash
Stars: ✭ 329 (-3.24%)
Mutual labels:  bioinformatics
Pyfaidx
Efficient pythonic random access to fasta subsequences
Stars: ✭ 307 (-9.71%)
Mutual labels:  bioinformatics

.. image:: https://github.com/marcelm/cutadapt/workflows/CI/badge.svg :target: https://travis-ci.org/marcelm/cutadapt :alt:

.. image:: https://img.shields.io/pypi/v/cutadapt.svg?branch=master :target: https://pypi.python.org/pypi/cutadapt :alt:

.. image:: https://codecov.io/gh/marcelm/cutadapt/branch/master/graph/badge.svg :target: https://codecov.io/gh/marcelm/cutadapt :alt:

.. image:: https://img.shields.io/badge/install%20with-bioconda-brightgreen.svg?style=flat :target: http://bioconda.github.io/recipes/cutadapt/README.html :alt: install with bioconda

======== Cutadapt

Cutadapt finds and removes adapter sequences, primers, poly-A tails and other types of unwanted sequence from your high-throughput sequencing reads.

Cleaning your data in this way is often required: Reads from small-RNA sequencing contain the 3’ sequencing adapter because the read is longer than the molecule that is sequenced. Amplicon reads start with a primer sequence. Poly-A tails are useful for pulling out RNA from your sample, but often you don’t want them to be in your reads.

Cutadapt helps with these trimming tasks by finding the adapter or primer sequences in an error-tolerant way. It can also modify and filter single-end and paired-end reads in various ways. Adapter sequences can contain IUPAC wildcard characters. Cutadapt can also demultiplex your reads.

Cutadapt is available under the terms of the MIT license.

Cutadapt development was started at TU Dortmund University <https://www.tu-dortmund.de>_ in the group of Prof. Dr. Sven Rahmann <https://www.rahmannlab.de/>. It is currently being developed within NBIS (National Bioinformatics Infrastructure Sweden) <https://nbis.se/>.

If you use Cutadapt, please cite DOI:10.14806/ej.17.1.200 <http://dx.doi.org/10.14806/ej.17.1.200>_ .

Links

  • Documentation <https://cutadapt.readthedocs.io/>_
  • Source code <https://github.com/marcelm/cutadapt/>_
  • Report an issue <https://github.com/marcelm/cutadapt/issues>_
  • Project page on PyPI (Python package index) <https://pypi.python.org/pypi/cutadapt/>_
  • Follow @marcelm_ on Twitter <https://twitter.com/marcelm_>_
  • Wrapper for the Galaxy platform <https://github.com/galaxyproject/tools-iuc/tree/master/tools/cutadapt>_
Note that the project description data, including the texts, logos, images, and/or trademarks, for each open source project belongs to its rightful owner. If you wish to add or remove any projects, please contact us at [email protected].