umi-tools

Tools for handling Unique Molecular Identifiers in NGS data sets

Science Score: 59.0%

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Low similarity (12.3%) to scientific vocabulary

Keywords from Contributors

human-cell-atlas single-cell-genomics single-cell-rna-seq quality-control lesson bioconda bioinformatics multiqc pypi reporting

Last synced: 6 months ago · JSON representation

Repository

Tools for handling Unique Molecular Identifiers in NGS data sets

Basic Info

Host: GitHub
Owner: CGATOxford
License: mit
Language: Python
Default Branch: master
Size: 29.8 MB

Statistics

Stars: 515
Watchers: 33
Forks: 197
Open Issues: 24
Releases: 34

Created almost 11 years ago · Last pushed 8 months ago

Metadata Files

Readme License

README.rst

.. image:: https://user-images.githubusercontent.com/6096414/93030687-c7cf7300-f61c-11ea-92b8-102ec17ef6aa.png

UMI-tools was published in `Genome Research `_ on 18 Jan '17 (open access)

For full documentation see https://umi-tools.readthedocs.io/en/latest/

Tools for dealing with Unique Molecular Identifiers
====================================================

This repository contains tools for dealing with Unique Molecular
Identifiers (UMIs)/Random Molecular Tags (RMTs) and single cell
RNA-Seq cell barcodes. Currently there are 6
commands. 

The ``extract`` and ``whitelist`` commands are used to prepare a
fastq containg UMIs +/- cell barcodes for alignment. 

* whitelist:
   **Builds a whitelist of the 'real' cell barcodes**
      This is useful for droplet-based single cell RNA-Seq where the
      identity of the true cell barcodes is unknown. Whitelist can
      then be used to filter with extract (see below)

* extract:
   **Flexible removal of UMI sequences from fastq reads.**
      UMIs are removed and appended to the read name. Any other
      barcode, for example a library barcode, is left on the read. Can
      also filter reads by quality or against a whitelist (see above)

The remaining commands, ``group``, ``dedup`` and ``count``/``count_tab``, are used to
identify PCR duplicates using the UMIs and perform different levels of
analysis depending on the needs of the user. A number of different UMI
deduplication schemes are enabled - The recommended method is
*directional*.

* dedup:
   **Groups PCR duplicates and deduplicates reads to yield one read per group**
      Use this when you want to remove the PCR duplicates prior to any
      downstream analysis

* group: 
   **Groups PCR duplicates using the same methods available through `dedup`.**
      This is useful when you want to manually interrogate the PCR duplicates
   
* count:
   **Groups and deduplicates PCR duplicates and counts the unique molecules per gene**
      Use this when you want to obtain a matrix with unique molecules
      per gene, per cell, for scRNA-Seq.

* count_tab:
   **As per count except input is a flatfile**

See `QUICK_START.md <./doc/QUICK_START.md>`_ for a quick tutorial on
the most common usage pattern.

If you want to use UMI-tools in single-cell RNA-Seq data processing,
see `Single_cell_tutorial.md <./doc/Single_cell_tutorial.md>`_

**Important update**: We now recommend the use of `alevin` for droplet-based
scRNA-Seq (e.g 10X, inDrop etc). `alevin` is an accurate, fast and convenient end-to-end tool to go from fastq -> count matrix and  extends the UMI error correction in `UMI-tools` within a framework that also enables quantification of droplet scRNA-Seq without discarding multi-mapped reads.  See `alevin documentation `_ and `alevin pre-print `_ for more information

The ``dedup``, ``group``, and ``count`` / ``count_tab`` commands make use of network-based methods to resolve similar UMIs with the same alignment coordinates. For a background regarding these methods see:

`Genome Research Publication `_

`Blog post discussing network-based methods `_.


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

If you're using Conda, you can use:

.. code:: bash

   $ conda install -c bioconda -c conda-forge umi_tools

Or pip:

.. code:: bash

   $ pip install umi_tools


Or if you'd like to work directly from the git repository:

.. code:: bash

   $ git clone https://github.com/CGATOxford/UMI-tools.git

Enter repository and run:

.. code:: bash

   $ python setup.py install

For more detail see `INSTALL.rst <./doc/INSTALL.rst>`_

Help
----- 

For full documentation see https://umi-tools.readthedocs.io/en/latest/

See `QUICK_START.md <./doc/QUICK_START.md>`_ and
`Single_cell_tutorial.md <./doc/Single_cell_tutorial.md>`_ for tutorials on the most common usage patterns.

To get help on umi_tools run

.. code:: bash

   $ umi_tools --help

To get help on the options for a specific [COMMAND], run

.. code:: bash

   $ umi_tools [COMMAND] --help


Dependencies
------------
umi_tools is dependent on `python>=3.5`, `numpy`, `pandas`, `scipy`, `cython`, `pysam`,
`future`, `regex` and `matplotlib`

Owner

Name: CGAT
Login: CGATOxford
Kind: organization
Email: andreas.heger@gmail.com
Location: Oxford, UK

Website: www.cgat.org
Repositories: 10
Profile: https://github.com/CGATOxford

GitHub Events

Total

Issues event: 29
Watch event: 29
Issue comment event: 66
Push event: 9
Pull request event: 9
Fork event: 7

Last Year

Issues event: 29
Watch event: 29
Issue comment event: 66
Push event: 9
Pull request event: 9
Fork event: 7

Committers

Last synced: over 2 years ago

All Time

Total Commits: 705
Total Committers: 37
Avg Commits per committer: 19.054
Development Distribution Score (DDS): 0.521

Past Year

Commits: 11
Committers: 4
Avg Commits per committer: 2.75
Development Distribution Score (DDS): 0.364

Top Committers

Name	Email	Commits
TomSmithCGAT	t**8@c**k	338
Tom Smith	t**2@d**k	150
IanSudbery	i**y@d**k	92
Tom Smith	T****T	36
Ian Sudbery	5****y	20
Ian Sudbery	i**y@s**k	11
Tom Smith	t**8@w**k	7
Gabriel Pratt	g**t@u**u	7
Matthew Parker	m**2@s**k	6
Stephen Kitcatt	s**t@c**k	4
Ye Chang	y**0@g**m	3
jz314	j****4	2
Peter Chovanec	p****5	2
jbloom	j**m@f**g	2
Mike Jackson	m**j@e**k	2
k3yavi	a**a@s**u	2
Christian Otto	c**f@g**m	1
Daniel Liu	d**2@g**m	1
Andreas Heger	a**r@g**m	1
Messerschmidt	c**t@c**e	1
Jan Oppelt	o**k@g**m	1
Frank Reinecke	f**e@q**m	1
Johannes Köster	j**r@t**e	1
akmorrow13	a**w@b**u	1
Sascha	s**s@h**m	1
redst4r	r**r@w**e	1
James Oguya	o**s@g**m	1
Hoohm	p**i@g**m	1
bowhan	b**n@i**m	1
Yu Fu	y****u	1
and 7 more...

Committer Domains (Top 20 + Academic)

sheffield.ac.uk: 2 dpag.ox.ac.uk: 2 linuxmail.org: 1 brueffer.io: 1 berkeley.edu: 1 tu-dortmund.de: 1 qiagen.com: 1 charite.de: 1 stonybrook.edu: 1 epcc.ed.ac.uk: 1 fredhutch.org: 1 cruk.manchester.ac.uk: 1 ucsd.edu: 1 workstation-tom.sysbiol.private.cam.ac.uk: 1 cam.ac.uk: 1

Issues and Pull Requests

Last synced: 6 months ago

All Time

Total issues: 168
Total pull requests: 54
Average time to close issues: about 1 year
Average time to close pull requests: 4 months
Total issue authors: 138
Total pull request authors: 14
Average comments per issue: 4.68
Average comments per pull request: 2.07
Merged pull requests: 43
Bot issues: 0
Bot pull requests: 0

Past Year

Issues: 15
Pull requests: 5
Average time to close issues: about 2 months
Average time to close pull requests: 3 months
Issue authors: 13
Pull request authors: 5
Average comments per issue: 1.0
Average comments per pull request: 1.6
Merged pull requests: 4
Bot issues: 0
Bot pull requests: 0

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Top Authors

Issue Authors

alexander-e-f-smith (7)
wangjiawen2013 (4)
IanSudbery (4)
kvn95ss (3)
YichaoOU (3)
kalavattam (3)
anoronh4 (3)
Rayan21100 (2)
TomSmithCGAT (2)
robinycfang (2)
yueli8 (2)
chrarnold (2)
lcabus-flomics (2)
hazmup (2)
NordinZandhuis (2)

Pull Request Authors

TomSmithCGAT (25)
IanSudbery (19)
eachanjohnson (5)
opplatek (3)
akmorrow13 (2)
sshen8 (2)
mfansler (1)
epruesse (1)
user-tq (1)
TyberiusPrime (1)
sebastian-luna-valero (1)
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msto (1)
6x7p3 (1)
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Top Labels

Issue Labels

Next release (4) Documentation (2) todo (2) enhancement (1) bug (1)

Pull Request Labels

Packages

Total packages: 3
Total downloads:
- pypi 2,269 last-month
Total docker downloads: 9,274

Total dependent packages: 4
(may contain duplicates)
Total dependent repositories: 6
(may contain duplicates)
Total versions: 47
Total maintainers: 4

pypi.org: umi-tools

umi_tools: Tools for UMI analyses

Homepage: https://github.com/CGATOxford/UMI-tools
Documentation: https://umi-tools.readthedocs.io/
License: MIT
Latest release: 1.1.6
published over 1 year ago

Versions: 41
Dependent Packages: 4
Dependent Repositories: 5
Downloads: 2,260 Last month
Docker Downloads: 9,274

Rankings

Docker downloads count: 1.5%

Dependent packages count: 1.9%

Stargazers count: 3.0%

Forks count: 3.7%

Average: 3.8%

Downloads: 6.0%

Dependent repos count: 6.6%

Maintainers (2)

toms IanSudbery

Last synced: 7 months ago

spack.io: py-umi-tools

Tools for handling Unique Molecular Identifiers in NGS data sets

Homepage: https://github.com/CGATOxford/UMI-tools
License: []
Latest release: 1.1.4
published over 2 years ago

Versions: 5
Dependent Packages: 0
Dependent Repositories: 0

Rankings

Dependent repos count: 0.0%

Forks count: 7.2%

Stargazers count: 10.8%

Average: 18.8%

Dependent packages count: 57.3%

Maintainers (1)

adamjstewart

Last synced: 7 months ago

pypi.org: umi-tools-csgx

umi_tools: Tools for UMI analyses

Homepage: https://github.com/CGATOxford/UMI-tools
Documentation: https://umi-tools-csgx.readthedocs.io/
License: MIT
Latest release: 1.1.1
published over 4 years ago

Versions: 1
Dependent Packages: 0
Dependent Repositories: 1
Downloads: 9 Last month

Rankings

Stargazers count: 3.0%

Forks count: 3.7%

Dependent packages count: 10.0%

Average: 20.2%

Dependent repos count: 21.8%

Downloads: 62.4%

Maintainers (1)

wikiselev

Last synced: 7 months ago

Dependencies

doc/requirements.txt pypi

future *
matplotlib *
numpy >=1.7
pandas >=0.12.0
pysam >=0.9
regex *
scipy *
setuptools >=1.1
six *
sphinx-markdown-tables *

requirements.txt pypi

future *
matplotlib *
numpy >=1.7
pandas >=0.12.0
pybktree *
pysam >=0.16.0.1
python >=3.5
regex *
scipy *
setuptools >=1.1
six *