PICor: Statistical Isotope Correction
ICor 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:
$ pip install picor
You need to have pandas and scipy installed.
Usage
After importing PICor and loading your data (for example a csv file) with pandas you the correction works with:
import pandas as pd
import picor
raw_data = pd.read_csv("data.csv", index="Time in h"))
corr_data = picor.calc_isotopologue_correction(
raw_data,
"NAD",
)
print(corr_data)
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.
Jørn Dietze, UiT - The Arctic University of Tromsø, 2020
Release files for PICor 0.3.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| PICor-0.3.2.tar.gz | 38.4 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| PICor-0.3.2-py2.py3-none-any.whl | Python 2, Python 3 | none | any | Details |
Total release size:61.4 kB
Release files / PICor-0.3.2.tar.gz
| Download URL | PICor-0.3.2.tar.gz |
|---|---|
| Size | 38.4 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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twine/3.2.0 pkginfo/1.6.1 requests/2.24.0 setuptools/50.0.0.post20200830 requests-toolbelt/0.9.1 tqdm/4.51.0 CPython/3.8.5
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Release files / PICor-0.3.2-py2.py3-none-any.whl
| Download URL | PICor-0.3.2-py2.py3-none-any.whl |
|---|---|
| Size | 23.1 kB |
| Tags | Python 2 Python 3 |
|
SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.2.0 pkginfo/1.6.1 requests/2.24.0 setuptools/50.0.0.post20200830 requests-toolbelt/0.9.1 tqdm/4.51.0 CPython/3.8.5
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