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Merge pull request #6 from compomics/ccs2im
Allow ion mobility output
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.github/workflows/publish.yml

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name: Publish
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on:
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workflow_dispatch:
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release:
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types: [created]
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jobs:
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publish:
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runs-on: ubuntu-latest
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environment:
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name: pypi
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url: https://pypi.org/p/im2deep
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permissions:
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id-token: write
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steps:
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- uses: actions/checkout@v4
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- name: Set up Python
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uses: actions/setup-python@v4
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with:
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python-version: "3.8"
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- name: Install dependencies
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run: |
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python -m pip install --upgrade pip build
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- name: Build
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run: python -m build
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- name: Install
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run: pip install dist/im2deep-*.whl
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- name: Test package
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run: |
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im2deep --help
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- name: Publish to PyPI
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uses: pypa/gh-action-pypi-publish@release/v1
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name: Publish
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on:
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workflow_dispatch:
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release:
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types: [created]
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jobs:
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publish:
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runs-on: ubuntu-latest
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environment:
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name: pypi
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url: https://pypi.org/p/im2deep
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permissions:
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id-token: write
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steps:
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- uses: actions/checkout@v4
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- name: Set up Python
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uses: actions/setup-python@v4
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with:
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python-version: "3.8"
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- name: Install dependencies
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run: |
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python -m pip install --upgrade pip build
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- name: Build
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run: python -m build
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- name: Install
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run: pip install dist/im2deep-*.whl
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- name: Test package
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run: |
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im2deep --help
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- name: Publish to PyPI
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uses: pypa/gh-action-pypi-publish@release/v1

.gitignore

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.vscode/
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.pytest_cache/
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IM2Deep.code-workspace
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# Testing
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test_data/

LICENSE

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MANIFEST.in

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include im2deep/models/*
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include im2deep/models/**/*
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include im2deep/reference_data/*
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include im2deep/models/*
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include im2deep/models/**/*
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include im2deep/reference_data/*

README.md

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# IM2Deep
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Collisional cross-section prediction for (modified) peptides.
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---
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## Introduction
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IM2Deep is a CCS predictor for (modified) peptides.
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It is able to accurately predict CCS for modified peptides, even if the modification wasn't observed during training.
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## Installation
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Install with pip:
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`pip install im2deep`
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## Usage
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### Basic CLI usage:
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```sh
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im2deep <path/to/peptide_file.csv>
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```
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If you want to calibrate your predictions (HIGHLY recommended), please provide a calibration file:
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```sh
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im2deep <path/to/peptide_file.csv> --calibration_file <path/to/peptide_file_with_CCS.csv>
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```
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For an overview of all CLI arguments, run `im2deep --help`.
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## Input files
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Both peptide and calibration files are expected to be comma-separated values (CSV) with the following columns:
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- `seq`: unmodified peptide sequence
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- `modifications`: every modifications should be listed as `location|name`, separated by a pipe character (`|`)
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between the location, the name, and other modifications. `location` is an integer counted starting at 1 for the
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first AA. 0 is reserved for N-terminal modifications, -1 for C-terminal modifications. `name` has to correspond
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to a Unimod (PSI-MS) name.
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- `charge`: peptide precursor charge
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- `CCS`: collisional cross-section (only for calibration file)
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For example:
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```csv
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seq,modifications,charge,CCS
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VVDDFADITTPLK,,2,422.9984309464991
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GVEVLSLTPSFMDIPEK,12|Oxidation,2,464.6568644356109
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SYSGREFDDLSPTEQK,,2,468.9863221739147
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SYSQSILLDLTDNR,,2,460.9340710819608
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DEELIHLDGK,,2,383.8693416055445
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IPQEKCILQTDVK,5|Butyryl|6|Carbamidomethyl,3,516.2079366048176
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```
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# IM2Deep
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Collisional cross-section prediction for (modified) peptides.
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---
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## Introduction
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IM2Deep is a CCS predictor for (modified) peptides.
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It is able to accurately predict CCS for modified peptides, even if the modification wasn't observed during training.
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## Installation
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Install with pip:
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`pip install im2deep`
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## Usage
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### Basic CLI usage:
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```sh
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im2deep <path/to/peptide_file.csv>
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```
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If you want to calibrate your predictions (HIGHLY recommended), please provide a calibration file:
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```sh
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im2deep <path/to/peptide_file.csv> --calibration_file <path/to/peptide_file_with_CCS.csv>
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```
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For an overview of all CLI arguments, run `im2deep --help`.
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## Input files
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Both peptide and calibration files are expected to be comma-separated values (CSV) with the following columns:
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- `seq`: unmodified peptide sequence
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- `modifications`: every modifications should be listed as `location|name`, separated by a pipe character (`|`)
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between the location, the name, and other modifications. `location` is an integer counted starting at 1 for the
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first AA. 0 is reserved for N-terminal modifications, -1 for C-terminal modifications. `name` has to correspond
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to a Unimod (PSI-MS) name.
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- `charge`: peptide precursor charge
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- `CCS`: collisional cross-section (only for calibration file)
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For example:
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```csv
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seq,modifications,charge,CCS
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VVDDFADITTPLK,,2,422.9984309464991
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GVEVLSLTPSFMDIPEK,12|Oxidation,2,464.6568644356109
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SYSGREFDDLSPTEQK,,2,468.9863221739147
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SYSQSILLDLTDNR,,2,460.9340710819608
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DEELIHLDGK,,2,383.8693416055445
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IPQEKCILQTDVK,5|Butyryl|6|Carbamidomethyl,3,516.2079366048176
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```
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