RT Alignment and Peptide ID Confidence Updating for LC-MS/MS Data
Project description
DART-ID
Website: https://slavovlab.github.io/DART-ID/
Manuscript: https://www.biorxiv.org/content/10.1101/399121v3
Getting started
Dependencies
DART-ID requires Python >= 3.4, and has been tested on Windows 8 / OSX Mojave 10.14 / Centos 7 / Ubuntu 14.04.
Installation
pip install dart-id
Usage
DART-ID requires a YAML-formatted configuration file to run. An example annotated config file can be found in example/config_annotated.yaml. You can specify input files and the output folder on the command line, if that's what you prefer.
View the command-line arguments anytime by running: dart_id -h
.
usage: dart_id [-h] [-i INPUT [INPUT ...]] [-o OUTPUT] [-v] [--version] -c
CONFIG_FILE
optional arguments:
-h, --help show this help message and exit
-i INPUT [INPUT ...], --input INPUT [INPUT ...]
Input file(s) from search engine output (e.g.,
MaxQuant evidence.txt). Not required if input files
are specified in the config file
-o OUTPUT, --output OUTPUT
Path to output folder
-v, --verbose
--version Display the program's version
-c CONFIG_FILE, --config-file CONFIG_FILE
Path to config file (required). See
example/config_example.yaml
Example runs
An example configuration file can be downloaded from GitHub: https://github.com/SlavovLab/DART-ID/blob/master/config_files/example_sqc_67_95_varied.yaml.
The first few lines of the above configuration file specify the path to the input file:
## Input
## ==========================
input:
- /path/to/SQC_67_95_Varied/evidence.txt
You can download the evidence.txt
file from MassIVE: ftp://massive.ucsd.edu/MSV000083149/other/MaxQuant/SQC_67_95_Varied/evidence.txt.
Then edit the path to the file downloaded, and run the following command:
dart_id -c config_files/example_sqc_67_95_varied.yaml -o ~/DART_ID/SQC_67_95_varied_20181206
The -o
parameter points to the output folder for DART-ID. You can also specify this path in the config file.
An example analysis of the data and configuration file specified above is available publicly at ftp://massive.ucsd.edu/MSV000083149/other/Alignments/SQC_varied_20180711_4/.
About the project
DART-ID is a project developed in the Slavov Laboratory at Northeastern University Bioengineering, and was authored by Albert Tian Chen, Alexander Franks (of UCSB Statistics and Applied Probability), and Nikolai Slavov.
The manuscript for this tool is available on bioRxiv: https://www.biorxiv.org/content/10.1101/399121v3.
Contact the authors by email: nslavov{at}northeastern.edu.
License
DART-ID is distributed by an MIT license.
Contributing
Please feel free to contribute to this project by opening an issue or pull request in the GitHub repository.
Data
All data used for the manuscript is available on UCSD's MassIVE Repository
Figures/Analysis
Scripts for the figures in the DART-ID manuscript are available in a separate GitHub repository, https://github.com/SlavovLab/DART-ID_2018
Project details
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