SEMQuant

This repository contains tools for SEMQuant developed by Biocomputing-Research-Group. These include Raxport, SiprosEnsemble, DIANN and some other scripts.

Overview

This repository contains tools for SEMQuant developed by Biocomputing-Research-Group. These include Raxport, SiprosEnsemble, Sipros5 and some scripts. there are two pipeline for SEMQuant: SEMQUant-DDA and SEMQuant-Astral.

Table of Contents

• SEMQUant-DDA
• SEMQuant-Astral

SEMQuant-DDA

SEMQuant-DDA

Install environment

Raxport relies on .net. Some scripts rely on python2, python3, and R.

conda create -n py2 scikit-learn python=2.7
conda create -n mono -c conda-forge mono
conda create -n py3 python=3.10

Raxport relies on .net. Some other scripts rely on python2, python3, and R.

Make folder for the workflow

export work_dir=/PATH_TO_YOUR_WORK_DIR
export tool_dir=/PATH_TO_SEMQUANT_DIR/SEMQuant/SEMQuant-DDA

#generate the following folder under your work_dir 
mkdir raw samples results 

### Download raw file

``` bash
cd raw 
# Download raw file with 2fmol yeast-ups1 in your work_dir
wget ftp://ftp.pride.ebi.ac.uk/pride/data/archive/2020/01/PXD002099/*_2fmol*.raw

The raw folder should contain 3 samples.

Convert raw to FT2

$tool_dir/Raxport -i $work_dir/raw -o $work_dir/raw
#conda activate mono

Generate Reverse Sequences

python $tool_dir/Script/sipros_prepare_protein_database.py -i work_dir/yeast_ups.fasta -o yeast_ups_rev.fasta -c tool_dir/configs/SiprosConfig_yeast.cfg
#replace yeast_ups.fasta with YOUR_DB.fasta, also for the output : yeast_ups_rev.fasta to YOUR_DB_rev.fasta
#need to update the FASTA_Database path in .cfg file 
FASTA_Database = work_dir/db_rev.fasta

The step will generate a new database file with reverse sequences. Update the path of FASTA_Database in the configuration file.

Running The Database-searching

There are two two to run Sipros_OpemMP for database searching: one for running on a single MS2 file via -f and another another processing multiple MS2 files via -w workingdirectory.

#!/bin/bash

# Single MS2 file
Sipros_OpemMP -o output_dir -f ms_data -c SiprosConfig.cfg
$tool_dir/SiprosEnsembleOMP -o $work_dir/results -f $work_dir/raw/YOUR_MS2.FT2 -c $tool_dir/configs/SiprosConfig.cfg
# Multiple MS2 files in a working directory
Sipros_OpemMP -o output_dir -w $work_dir -c SiprosConfig.cfg
$tool_dir/SiprosEnsembleOMP -o $work_dir/results -w $work_dir/raw -c $tool_dir/configs/SiprosConfig.cfg

Results (.Spe2Pep files) will be saved on the output directory. if you have many configure files, specify -g, like Sipros_OpemMP -o output_dir -w workingdirectory -g configurefiledirectory. Use ./Sipros_OpemMP -h for help information.

conda activate py2

#prep sample for store results
cd $work_dir
for sample in result/2fmol/*Spe2Pep.txt; do path=${sample%.SE*}; name=${path#result/}; mkdir samples_2fmol/${name}; done

for sample in result/2fmol/*Spe2Pep.txt; do path=${sample%.SE*}; name=${path#result/}; cp ${sample} samples_2fmol/${name}/${sample#result/2fmol/}; done

for folder in $work_dir/result/samples_2fmol/*/; do echo ${folder}; done

### filter PSMs
for folder in $work_dir/result/samples_2fmol/*/; do ./runSiprosFiltering.sh  -in ${folder} -c ../configs/SiprosConfig_yeast.cfg -o ${folder}; mv ${folder}/*.p*.txt ${folder}/peptide/;mv ${folder}/*.tab ${folder}/peptide/; done
for folder in $work_dir/result/samples_2fmol/*/; do ./runSiprosFiltering.sh  -in ${folder} -c ../configs/SiprosConfig_yeast.cfg -o ${folder}; done

# filter for pep 1 %
mkdir PEP_1pct
cp *peptide.tsv PEP_1pct/
for folder in $work_dir/result/samples_2fmol/110*/; do cp ${folder}/*.SE.pep.txt ./PEP_1pct; done
ls -la PEP_1pct/

for folder in $work_dir/result/samples_2fmol/*_01/ ;do python $tool_dir/Script/sipros_ensemble_filtering.py -i ${folder} -c $tool_dir/configs/SiprosConfig.cfg -o ${folder}; done


for folder in $work_dir/result/samples_2fmol/*_01/; do python $tool_dir/Script/Sipros_peptides_assembling.py  -c /$tool_dir/configs/SiprosConfig.cfg -w ${folder}; done

IonQuant for quantification

conda activate mono

java -Xmx21G -Dlibs.bruker.dir=$tool_dir/bruker -Dlibs.thermo.dir=$tool_dir/thermo -cp $tools_dir/jfreechart-1.5.3.jar:$tools_dir/batmass-io-1.30.0.jar:/$tools_dir/IonQuant-1.10.12.jar ionquant.IonQuant --threads 23 --perform-ms1quant 1 --perform-isoquant 0 --isotol 20.0 --isolevel 2 --isotype tmt10 --ionmobility 0 --site-reports 1 --minexps 1 --mbr 1 --maxlfq 1 --requantify 1 --mztol 10 --imtol 0.05 --rttol 0.4 --mbrmincorr 0 --mbrrttol 1 --mbrimtol 0.05 --mbrtoprun 40 --ionfdr 0.01 --proteinfdr 0.01 --peptidefdr 0.01 --normalization 1 --minisotopes 2 --minscans 3 --writeindex 0 --tp 0 --minfreq 0 --minions 2 --locprob 0.75 --uniqueness 0 --multidir . --filelist $tool_dir/filelist_ionquant.txt --modlist $tool_dir/modmasses_ionquant.txt

SEMQuant-Astral

SEMQuant-Astral

Make folder for the workflow

#work_dir = YOUR_WORKING_DIRECTORY
export work_dir=/PATH_TO_YOUR_WORK_DIR
export tool_dir=/PATH_TO_SEMQUANT_DIR/SEMQuant/SEMQuant-Astral
# generate the following folder under your work_dir 
mkdir raw samples results 

### Download raw file

``` bash
cd raw 
# Download raw file with three-mixed species Astral data - E45 in your work_dir
wget ftp://www.ebi.ac.uk/pride/archive/projects/PXD046444/20230324_OLEP08_200ng_30min_E45H50Y5*.raw

The raw folder should contain 3 samples.

Convert raw to FT2 use Raxport

conda activate mono
# -j is the threads that you plan to use
# -f set the spectra output format to indexed mzML
# -L select MS level to be MS2
mono ThermoRawFileParser.exe -d=./raw -o=./raw -f=2 -L=2 

Running The Database-searching

There are two ways to run Sipros_OpemMP for database searching: one for running on a single MS2 file via -f and another another processing multiple MS2 files via -w workingdirectory.

#!/bin/bash

# Single MS2 file
Sipros -o output_dir -f ms_data -c SiprosConfig.cfg
$tool_dir/Sipros -o $work_dir/results -f $work_dir/raw/YOUR_MS2.FT2 -c $tool_dir/configs/SiprosConfig.cfg
# Multiple MS2 files in a working directory
Sipros -o output_dir -w work_dir -c SiprosConfig.cfg
$tool_dir/Sipros -o $work_dir/results -w $work_dir/raw -c $tool_dir/configs/SiprosConfig.cfg

Use Rscript to generate PSM features for Percolator required input

Percolator

Percolator [Work dir: $work_dir/dataset/Astral/fragpipe_MBR/E45/2]
$tool_dir/percolator --only-psms --no-terminate --post-processing-tdc --num-threads 23 --results-psms 20230324_OLEP08_200ng_30min_E45H50Y5_180K_2Th3p5ms_02_percolator_target_psms.tsv --decoy-results-psms 20230324_OLEP08_200ng_30min_E45H50Y5_180K_2Th3p5ms_02_percolator_decoy_psms.tsv --protein-decoy-pattern rev_ 20230324_OLEP08_200ng_30min_E45H50Y5_180K_2Th3p5ms_02.pin

convert percolator output for protein inference input

python $tool_dir/Percolator2PeptideProphet.py ~/three-species/result_V2/SE_percolator_DIANN/E45/01/20230324_OLEP08_200ng_30min_E45H50Y5_180K_2Th3p5ms_01.target.Spe2Pep.txt ~/three-species/result_V2/SE_percolator_DIANN/E20/01/20230324_OLEP08_200ng_30min_E45H50Y5_180K_2Th3p5ms_01.pin ~/three-species/result_V2/SE_percolator_DIANN/E20/01/ 20230324_OLEP08_200ng_30min_E45H50Y5_180K_2Th3p5ms_01

Protein inference

ProteinProphet [Work dir: /home/UNT/bz0053/Documents/Projects/MBR/dataset/Astral/fragpipe_MBR/E45]
$tool_dir/philosopher_v5.1.0_linux_amd64/philosopher proteinprophet --maxppmdiff 2000000 --output combined $work_dir/E45/filelist_proteinprophet.txt

FDR control

#Process 'ProteinProphet' finished, exit code: 0
PhilosopherDbAnnotate [Work dir: F:\Astral\DIANN\E45]
$tool_dir/philosopher_v5.1.0_linux_amd64/philosopher database --annotate F:\Astral\2024-09-22-decoys-mix_HYE.fasta.fas --prefix rev_
Process 'PhilosopherDbAnnotate' finished, exit code: 0

#PhilosopherFilter [Work dir: F:\Astral\DIANN\E30]
$tools_dir/philosopher_v5.1.0_linux_amd64/philosopher filter --picked --prot 0.01 --minPepLen 8 --tag rev_ --pepxml F:\Astral\DIANN\E45 --protxml F:\Astral\DIANN\E45\combined.prot.xml --razor

generate spec lib

SpecLibGen [Work dir: F:\Astral\DIANN\E45]
python -u $tool_dir\speclib\gen_con_spec_lib.py F:\Astral\2024-09-22-decoys-mix_HYE.fasta.fas F:\Astral\DIANN\E45 unused F:\Astral\DIANN\E30 True unused use_easypqp noiRT;noIM 16 "--unimod $tool_dir/unimod_old.xml --max_delta_unimod 0.02 --max_delta_ppm 15.0 --fragment_types [\'b\',\'y\',]" "--rt_lowess_fraction 0.0" delete_intermediate_files $work_dir\E45\filelist_speclibgen.txt

DIANN for quantification

DIA-NN [Work dir: $work_dir/DIANN/E45]
$tool_dir/fragpipe/tools/diann/1.8.2_beta_8/linux/diann-1.8.1.8 --lib library.tsv --threads 15 --verbose 1 --out diann-output/report.tsv --qvalue 0.01 --matrix-qvalue 0.01 --matrices --no-prot-inf --smart-profiling --no-quant-files --peak-center --no-ifs-removal --report-lib-info --cfg $work_dir/E45/filelist_diann.txt--
DIA-NN 1.8.2 beta 8 (Data-Independent Acquisition by Neural Networks)

Citation