JUMPlib

• Introduction
• Basic Installation
• Input Data
• Sample Data
• Basic Installation
• JUMPlib Commands
• Test Data Exercise

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Introduction

JUMPlib is a specialized tool designed for searching TMT-based proteomics data. The JUMPlib program enables TMT library generation, database search, identification filtering, and protein quantification. To evaluate the performance of the JUMPlib program, we conducted an assessment using a large-scale TMT data set. In addition, the JUMPlib program can readily be adapted for label-free library generation and database search. Moreover, we curated comprehensive 11-plex and 18-plex TMT libraries from human brain samples, providing valuable resources to the research community.

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JUMPlib Publication:

• If you use JUMPlib as part of a publication, please include this reference https://pubs.acs.org/doi/full/10.1021/acs.jproteome.4c00410.

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Basic Installation

The installation is tested in the linux system and HPC servers but this should work properly in windows and mac too. We highly recommend installing JUMPspecLib in a virtual environment, for example using the anaconda or miniconda package manager

1. Create a virtual enviroment and install required packages.

Here are some commands that would create an anaconda python environment for running JUMPspecLib:

conda create -n jumplib python=3.8
conda activate jumplib
conda install numpy pandas=1.5.3 matplotlib scipy seaborn statsmodels pyteomics rpy2
# we recommend pandas=1.5.3 particular version of pandas because the libraries were created using this version but if you are going to create your own library using JUMPspecLib you can install latest version

2. Place the JUMPlib distribution source in the desired location (call this <path to JUMPlib>)

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• Obtaining JUMPspecLib source You can obtain the latest version of JUMPspecLib from git; simple clone the git repository:

    git clone https://github.com/surPoudel/JUMPspecLib.git

in the directory where you would like JUMPlib to be installed (call this directory <path to JUMPlib>). Note that JUMPlib does not support out-of-place installs; the JUMPlib git repository is the entire installation.

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JUMPlib Commands

Once the conda environment (JUMPlib) is activated

1. make a working directory
2. keep all the mzXML or mzML files in the same directory
3. copy the parameter file from parameterFiles to the same directory
4. make necessary changes for the parameters
5. Run the command below

a. Library generation

Preprocessing 
jump_lib -pp jump_lib_preprocess.params *.mzXML/*.mzML 

Library generation
jump_lib -d jump_lib_gen.params

Library merging
jump_lib -d_merge jump_lib_specLibMerge.params

Note: We also provide the comprehensive TMT libraries so you may skip Library generation becasue it takes time.

b. Library searching (with presearch and without presearch)

jump_lib -pp jump_preprocess.params *.mzXML/*.mzML
jump_lib -s jumplib_search.params
jump_lib -pp_s jumplib_search.params

c. Filter the search results

jump_lib -f jumplib_filter.params

d. Quantification of filtered dataset

jump_lib -q jump_lib_q.params

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Test Data Exercise

Download example_data

• This will download FTLD_Batch1_F20.mzXML with other required parameter files

Download spectral_libraries

• This will download TMT11 and TMT18 in .pkl file

  JUMPlib\spectral_libraries
  

• Contains TMT11 and TMT18 Human brain libraries

Test Data

• Go to

  example_data
  

• This folder contains a sample mzXML file along with parameter files required for search, filter and quantification
• It also has a script to wrap all at once (Change the path as required before you run the wrapper)

  bash run_jumplib.sh
  

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Maintainers

• To submit bug reports and feature suggestions, please contact

  Suresh Poudel ([email protected])

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