picor

Python Isotope Correction Package

https://github.com/molecularbioinformatics/picor

Science Score: 26.0%

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Low similarity (11.6%) to scientific vocabulary

Last synced: 11 months ago · JSON representation

Repository

Python Isotope Correction Package

Basic Info

Host: GitHub
Owner: MolecularBioinformatics
License: gpl-3.0
Language: Python
Default Branch: master
Size: 287 KB

Statistics

Stars: 6
Watchers: 4
Forks: 2
Open Issues: 6
Releases: 4

Created over 5 years ago · Last pushed 11 months ago

Metadata Files

Readme Changelog License Authors

PICor: Statistical Isotope Correction

PICor is a python package for correcting mass spectrometry data for the effect of natural isotope abundance.

Description

PICor takes pandas DataFrames of the measured integrated MS intensities as input, corrects them for natural isotope abundance and returns a DataFrame again.

PICor can also correct for overlapping isotopologues due to too low resoltion. For example, the 13-C4 and 2-H4 isotopologues of the metabolite NAD can't be resolved at a resolution of 60,000 at 200 m/z.

Installation

To install:

bash $ pip install picor

PICor depends on docopt, pandas, openpyxl and scipy and installs those with pip if not available.

Usage

You can use PICor in two ways:

Command Line

After the installation you can use PICor anywhere from the command line with picor.

bash picor tests/test_dataset.xlsx NAD -x "dummy column int" -x "dummy column str"

Files with .csv or .xlsx suffix can be used as input files. You can choose the output file (in csv format) with the -o option. If no output file is given, output will be printed to stdout.

picor -h shows all options.

Python Module

After importing PICor and loading your data (for example a csv file) with pandas you the correction works with:

```python import pandas as pd import picor

rawdata = pd.DataFrame( { "No label": {0: 100, 1: 200, 2: 300, 3: 400, 4: 500, 5: 600}, "1C13": {0: 100, 1: 100, 2: 100, 3: 100, 4: 100, 5: 100}, "4C13 6H02 3N15": {0: 30, 1: 40, 2: 50, 3: 60, 4: 70, 5: 80}, "dummy column str": {0: "C", 1: "ER", 2: "C", 3: "ER", 4: "C", 5: "ER"}, } ) corrdata = picor.calcisotopologuecorrection( rawdata, moleculename="NAD", excludecol=["dummy column str"], ) print(corrdata) ```

In case the DataFrame contains columns (except the index colum) with other data than raw measurements, you can use either the subset with a list of all columns to be used or exclude_col with a list of the column to be skipped.

You can activate a resolution depent correction by setting resolution_correction to True. Specify the resolution and the reference m/z ratio with resolution and mz_calibration.

Molecule Specification

The molecule to be corrected can either be specified by name (molecule_name) or by formula and charge (molecule_formula and molecule_charge). If a name is used it has to be specified in the file specified by molecules_file (file path).

The molecule file has to be tab-separated with the columns name, formula and charge. The column labels have to match exactly. Look at the example file ìn src/picor/metabolites.csv.

Input Data

Using the command line interface picor both excel (.xlsx) and comma-separated data (.csv) can be corrected.

Both data formats should be arranged with the different samples as rows and different labels/isotopologues as columns. Additional columns with for example more information about the samples have to be added to the excluded columns. Either with -x (command line) or exclude_col parameter as a list (python interface).

Example Data

| sample number | No label | 1C13 | 4C13 6H02 3N15 | sample condition | |:------------- | -------- | ---- | -------------- | ---------------- | | 0 | 100 | 100 | 30 | C | | 1 | 200 | 100 | 40 | ER | | 2 | 300 | 100 | 50 | C | | 3 | 400 | 100 | 60 | ER | | 4 | 500 | 100 | 70 | C | | 5 | 600 | 100 | 80 | ER |

Label Specification

The isotopologues or labels are specified as string in the table header (first line). Labels can include either one or multiple isotopes or 'No label'. The number of labeled atoms of each isotope has to be specified before the element, e.g. '3H02 2C13' for three deuterium and two 13-C atoms. Spaces and underscores are allowed but not necessary in the label definition.

In case you want to add additional information you can a prefix separated by a colon (':'), e.g. "NAD:2C13". The prefix will be ignored.

Jørn Dietze, UiT -The Arctic University of Norway, 2022

Owner

Name: MolecularBioinformatics
Login: MolecularBioinformatics
Kind: organization
Location: Norway

Repositories: 14
Profile: https://github.com/MolecularBioinformatics

GitHub Events

Total

Member event: 3
Push event: 1
Pull request event: 3
Create event: 1

Last Year

Member event: 3
Push event: 1
Pull request event: 3
Create event: 1

Committers

Last synced: over 2 years ago

All Time

Total Commits: 185
Total Committers: 4
Avg Commits per committer: 46.25
Development Distribution Score (DDS): 0.341

Past Year

Commits: 14
Committers: 2
Avg Commits per committer: 7.0
Development Distribution Score (DDS): 0.214

Top Committers

Name	Email	Commits
Joern Dietze	j**e@p**e	122
Joern Dietze	j**0@u**o	59
renovate[bot]	2****]	3
Mathias Bockwoldt	m**t@u**o	1

Committer Domains (Top 20 + Academic)

uit.no: 2 posteo.de: 1

Issues and Pull Requests

Last synced: 11 months ago

All Time

Total issues: 3
Total pull requests: 16
Average time to close issues: N/A
Average time to close pull requests: 4 months
Total issue authors: 3
Total pull request authors: 4
Average comments per issue: 0.0
Average comments per pull request: 0.19
Merged pull requests: 10
Bot issues: 1
Bot pull requests: 10

Past Year

Issues: 0
Pull requests: 4
Average time to close issues: N/A
Average time to close pull requests: N/A
Issue authors: 0
Pull request authors: 3
Average comments per issue: 0
Average comments per pull request: 0.0
Merged pull requests: 0
Bot issues: 0
Bot pull requests: 1

View more stats

Top Authors

Issue Authors

Danzelot (1)
renovate[bot] (1)
surajsept (1)

Pull Request Authors

renovate[bot] (10)
Danzelot (4)
surajsept (1)
mathiasbockwoldt (1)

Top Labels

Issue Labels

Pull Request Labels

Packages

Total packages: 1
Total downloads:
- pypi 34 last-month

Total dependent packages: 0
Total dependent repositories: 1
Total versions: 9
Total maintainers: 1

pypi.org: picor

Isotope correction for MS data

Homepage: https://github.com/MolecularBioinformatics/PICor
Documentation: https://picor.readthedocs.io/
License: gpl3
Latest release: 1.1.0
published over 3 years ago

Versions: 9
Dependent Packages: 0
Dependent Repositories: 1
Downloads: 34 Last month

Rankings

Dependent packages count: 10.0%

Forks count: 19.1%

Average: 21.3%

Dependent repos count: 21.7%

Stargazers count: 23.0%

Downloads: 32.4%

Maintainers (1)

jd-no

Last synced: 11 months ago

Dependencies

Pipfile pypi

black * develop
coverage * develop
flake8 * develop
ipython >=7.31.1 develop
pdbpp * develop
pylint * develop
pyscaffold * develop
pytest * develop
pytest-cov * develop
docopt *
pandas *
picor *
scipy *

Pipfile.lock pypi

appdirs ==1.4.4 develop
astroid ==2.9.3 develop
asttokens ==2.0.5 develop
attrs ==21.4.0 develop
backcall ==0.2.0 develop
black ==22.1.0 develop
click ==8.0.3 develop
configupdater ==3.0.1 develop
coverage ==6.3.1 develop
decorator ==5.1.1 develop
executing ==0.8.2 develop
fancycompleter ==0.9.1 develop
flake8 ==4.0.1 develop
iniconfig ==1.1.1 develop
ipython ==8.0.1 develop
isort ==5.10.1 develop
jedi ==0.18.1 develop
lazy-object-proxy ==1.7.1 develop
matplotlib-inline ==0.1.3 develop
mccabe ==0.6.1 develop
mypy-extensions ==0.4.3 develop
packaging ==21.3 develop
parso ==0.8.3 develop
pathspec ==0.9.0 develop
pdbpp ==0.10.3 develop
pexpect ==4.8.0 develop
pickleshare ==0.7.5 develop
platformdirs ==2.5.0 develop
pluggy ==1.0.0 develop
prompt-toolkit ==3.0.28 develop
ptyprocess ==0.7.0 develop
pure-eval ==0.2.2 develop
py ==1.11.0 develop
pycodestyle ==2.8.0 develop
pyflakes ==2.4.0 develop
pygments ==2.11.2 develop
pylint ==2.12.2 develop
pyparsing ==3.0.7 develop
pyrepl ==0.9.0 develop
pyscaffold ==4.1.4 develop
pytest ==7.0.1 develop
pytest-cov ==3.0.0 develop
setuptools-scm ==6.4.2 develop
six ==1.16.0 develop
stack-data ==0.2.0 develop
toml ==0.10.2 develop
tomli ==2.0.1 develop
tomlkit ==0.9.2 develop
traitlets ==5.1.1 develop
typing-extensions ==4.1.1 develop
wcwidth ==0.2.5 develop
wmctrl ==0.4 develop
wrapt ==1.13.3 develop
docopt ==0.6.2
et-xmlfile ==1.1.0
numpy ==1.22.2
openpyxl ==3.0.9
pandas ==1.4.1
picor *
python-dateutil ==2.8.2
pytz ==2021.3
scipy ==1.8.0
six ==1.16.0

.github/workflows/ci.yml actions

actions/checkout v2 composite
actions/setup-python v2 composite

environment.yml conda

black
coverage
docopt
flake8
ipython
pandas
pdbpp
pip
pylint
pyscaffold
pytest
pytest-cov
python >=3.6
scipy
tox

picor

Science Score: 26.0%

Repository

Basic Info

Statistics

Metadata Files

README.md

PICor: Statistical Isotope Correction

Description

Installation

Usage

Command Line

Python Module

Molecule Specification

Input Data

Example Data

Label Specification

Owner

GitHub Events

Total

Last Year

Committers

All Time

Past Year

Top Committers

Committer Domains (Top 20 + Academic)

Issues and Pull Requests

All Time

Past Year

Top Authors

Issue Authors

Pull Request Authors

Top Labels

Issue Labels

Pull Request Labels

Packages

pypi.org: picor

Rankings

Maintainers (1)

Dependencies