DIA data analysis

Overall summary

Name	Pub date	Dev stat	Stra.	x-first	Interface	Acce.
Ion Accounting [1]	2009 Mar.	/	R	/	/	C
ETISEQ [2]	2009 Aug.	Not	R	/	C	F
DeMux [3]	2009 Dec.	/	R	/	/	R
Skyline [4]	2010 Apr.	Active	L	C	C & G	O
FT-ARM [9]	2012 Jan.	Not	S/L	S	C & G	F
Spectronaut [10]	2013	Active	R,L	C	C & G	C
OpenSWATH [12]	2014 Mar.	Active	L	C	C & G	O
DIANA [13]	2014 Oct.	Not	L	C	C	O
DIA-Umpire [14]	2015 Jan.	Active	R,L	/,C	C & G	O
SWATHProphet [16]	2015 Feb.	Not	L	C	C	O
Group-DIA [17]	2015 Oct.	Not	R,L	/,C	C	O
MSPLIT-DIA [18]	2015 Nov.	Not	L	S	C	F
PECAN (Walnut) [19]	2017 Aug.	Active	S	S	C & G	O
Specter [20]	2018 Apr.	Not	L	S	C	O
EncyclopeDIA [21]	2018 Dec.	Active	L	S	C & G	O
DeepNovo-DIA [23]	2018 Dec.	Not	D	C	C	O
PEAKS [24]	2018	Active	S,L,D	N	C & G	C
DIA-NN [26]	2019 Nov.	Active	L	C	C & G	F
DIA tensor [32]	2020 Oct.	Not	I	/	C	F
MaxDIA [33]	2021 July	Active	L	C	C & G	F
DIAmeter [34]	2021 July	Active	S	S	C	O
FIGS [35]	2021 July	Not	L	S	C	O
mstc [36]	2021 July	Not	I	/	C	O
CsoDIAq [37]	2021 Sep.	Active	L	S	C & G	O
DreamDIAXMBD [38]	2021 Oct.	Not	L	C	C	O
Dear-DIAXMBD [39]	2023 June	Active	R	/	C & G	F
MSFragger-DIA [40]	2023 July	Active	S	S	C & G	F

Note

• Pub date (publication date): the date the tool was publicly released by publisher

  • Spectronaut is noted by its public release date (first publication was in 2015 [10])

  • PEAKS is noted by the date it supported the analysis of DIA data (PEAKS X in 2018)

  • MSFragger-DIA is noted by its related publication date (and the function has been available in 2020)

• Dev stat (development status)

  • Active: has update of any type in last one year (e.g. response of question from authors on GitHub issues, document update, bug fix, and feature update)

  • Not: not active

  • PECAN is re-implemented as Walnut and is being maintained and upgraded

• Stra. (analysis strategies) (note: some functions for analysis of other data type, like DDA, are not included)

  • R: spectra reconstruction

  • S: sequence-based search

  • L: library-based search

  • D: de novo sequencing

  • I: sequencing-independent

• x-first (spectrum-/chromatogram-first analysis approaches)

  • S: spectrum-first

  • C: chromatogram-first

  • N: unknown

  • /:

  • DIA-Umpire and Group-DIA work for two functions: 1. spectra reconstruction, which belongs to neither approach; 2. targeted re-extraction for quantification, which has a chromatogram-first approach

  • DeepNovo-DIA works for de novo sequencing

• (User) interface

  • C: command line interface (CLI)

  • G: graphical user interface (GUI)

  • Note: the following software get their GUI support from accompanying tools or platforms – OpenSWATH: TOPPAS, GALAXY; DIA-Umpire: FragPipe; PECAN (Walnut): EncyclopeDIA; MSFragger-DIA: FragPipe

• Acce. (accessibility)

  • C: commercial

  • F: free access

  • O: open source (whilst, free access)

  • R: need request from authors

  • N: not mentioned in the paper

Individuals

Ion Accounting

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Reference:

[1]

Database searching and accounting of multiplexed precursor and product ion spectra from the data independent analysis of simple and complex peptide mixtures. 10.1002/pmic.200800564

Full name	Ion Accounting
Authors	Guo-Zhong Li et al.
Lab & Company	Waters Corporation
Publication date	2009 Mar.
Analysis strategies	Spectra reconstruction and seqeunce-based search on extracted precursor-fragment ion pairs

Function:

spectra reconstruction + seqeunce-based search

Pre-processing	Ion detection based on 2D-convolution
Ion grouping criteria	Apex RT
Fragment assignment	One-to-multi (reassigned according to matching quality in sequence-based search step)

ETISEQ

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Reference:

[2]

ETISEQ - an algorithm for automated elution time ion sequencing of concurrently fragmented peptides for mass spectrometry-based proteomics. 10.1186/1471-2105-10-244

Full name	Elution Time Ion Sequencing
Authors	Jason WH Wong et al.
Lab & Company	Wong Lab
Publication date	2009 Aug.
Analysis strategies	Spectra reconstruction

Function:

spectra reconstruction

Pre-processing	Potential contaminant signal removing
Ion grouping criteria	PCC and cross-correlation lag
Fragment assignment	One-to-multi; 2. unmatched fragments are assigned to all precursor

DeMux

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Reference:

[3]

Deconvolution of Mixture Spectra from Ion-Trap Data-Independent-Acquisition Tandem Mass Spectrometry. 10.1021/ac901801b

Full name	DeMux
Authors	Marshall Bern et al.
Lab & Company	MacCoss Lab
Publication date	2009 Dec.
Analysis strategies	Spectra reconstruction

Function:

spectra reconstruction

Pre-processing	Coarse spectral binning
Ion grouping criteria	(No precursor requirement) correlation between m/z bins in MS2 spectral map
Fragment assignment	One-to-multi, but the cluster center (seed) is dropped in each iteration

Skyline

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Reference:

[4]

Skyline: an open source document editor for creating and analyzing targeted proteomics experiments. 10.1093/bioinformatics/btq054

[5]

A framework for installable external tools in Skyline. 10.1093/bioinformatics/btu148

[6]

Multiplexed peptide analysis using data-independent acquisition and Skyline. 10.1038/nprot.2015.055

[7]

Using Skyline to Analyze Data-Containing Liquid Chromatography, Ion Mobility Spectrometry, and Mass Spectrometry Dimensions. 10.1007/s13361-018-2028-5

[8]

The Skyline ecosystem: Informatics for quantitative mass spectrometry proteomics. 10.1002/mas.21540

Full name	Skyline
Home page	https://skyline.ms/project/home/software/Skyline/begin.view
Source code	https://github.com/ProteoWizard/pwiz
Programming language	C#
Authors	Brendan X. MacLean et al.
Lab & Company	MacCoss Lab
Publication date	2010 Apr.
Analysis strategies	Library-based search

Function:

Library-based search

Analysis approach	Chromatogram-first
Minimum scoring unit	Peak group
Scoring model	(mProphet) linear classifier; (Avant-Garde) combination of sub-scores with fixed parameters

FT-ARM

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Reference:

[9]

Accurate Peptide Fragment Mass Analysis: Multiplexed Peptide Identification and Quantification. 10.1021/pr2008175

Full name	FT-ARM
Home page	https://brucelab.gs.washington.edu/FT-ARM/index.html
Authors	Chad R. Weisbrod et al.
Lab & Company	Bruce Lab
Publication date	2012 Jan.
Analysis strategies	Sequence-/Library-based search

Function:

Sequence-/Library-based search

Analysis approach	Spectrum-first
SSM score	Dot product
Used prior information	(optional) fragmentation pattern

Spectronaut

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Reference:

[10] (1,2)

Extending the Limits of Quantitative Proteome Profiling with Data-Independent Acquisition and Application to Acetaminophen-Treated Three-Dimensional Liver Microtissues. 10.1074/mcp.M114.044305

Introduced PTM scoring in version 13:

[11]

Rapid and site-specific deep phosphoproteome profiling by data-independent acquisition without the need for spectral libraries. 10.1038/s41467-020-14609-1

Full name	Spectronaut
Home page	https://biognosys.com/software/spectronaut
Programming language	C#
Authors	Roland Bruderer et al.
Lab & Company	Biognosys AG
Release date	2013
Analysis strategies	Spectra reconstruction and sequence-based search on pseudo spectra; Library-based search

OpenSWATH

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Reference:

[12]

OpenSWATH enables automated, targeted analysis of data-independent acquisition MS data. 10.1038/nbt.2841

Full name	OpenSWATH
Home page	http://openswath.org
Source code	https://github.com/OpenMS/OpenMS
Programming language	C++ & Python
Authors	Hannes L. Röst et al.
Lab & Company	Aebersold Lab & Röst Lab
Publication date	2014 Mar.
Analysis strategies	Library-based search

Function:

Library-based search

Analysis approach	Chromatogram-first
Minimum scoring unit	Peak group
Scoring model	(PyProphet) XGBoost

DIANA

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Reference:

[13]

DIANA-algorithmic improvements for analysis of data-independent acquisition MS data. 10.1093/bioinformatics/btu686

Full name	DIANA
Home page	https://proteomics.immunoprot.lth.se
Programming language	Scala & Python
Authors	Johan Teleman et al.
Lab & Company	Levander Lab
Publication date	2014 Oct.
Analysis strategies	Library-based search

Function:

Library-based search

Analysis approach	Chromatogram-first
Minimum scoring unit	Peak group
Scoring model	(PyProphet) XGBoost

DIA-Umpire

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Reference:

[14]

DIA-Umpire: comprehensive computational framework for data-independent acquisition proteomics. 10.1038/nmeth.3255

[15]

Untargeted, spectral library-free analysis of data-independent acquisition proteomics data generated using Orbitrap mass spectrometers. 10.1002/pmic.201500526

Full name	DIA-Umpire
Home page	https://diaumpire.nesvilab.org
Source code	https://github.com/Nesvilab/DIA-Umpire
Programming language	Java
Authors	Chih-Chiang Tsou et al.
Lab & Company	Nesvizhskii Lab
Publication date	2015 Jan.
Analysis strategies	Spectra reconstruction; library-based search

Function:

spectra reconstruction

Pre-processing	Interpolation and unimodal peak splitting
Ion grouping criteria	summed mass of two fragments equals to precursor mass; 2. precursor-fragment PCC rank and apex RT
Fragment assignment	One-to-multi

SWATHProphet

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Reference:

[16]

Automated Validation of Results and Removal of Fragment Ion Interferences in Targeted Analysis of Data-independent Acquisition Mass Spectrometry (MS) using SWATHProphet. 10.1074/mcp.O114.044917

Full name	SWATHProphet
Home page	http://tools.proteomecenter.org/wiki/index.php?title=Software:SWATHProphet
Source code	https://sourceforge.net/projects/sashimi/files/
Programming language	Perl
Authors	Andrew Keller et al.
Lab & Company	Moritz Lab
Publication date	2015 Feb.
Analysis strategies	Library-based search

Function:

Library-based search

Analysis approach	Chromatogram-first
Minimum scoring unit	Peak group
Scoring model	mProphet-like linear classifier

Group-DIA

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Reference:

[17]

Group-DIA: analyzing multiple data-independent acquisition mass spectrometry data files. 10.1038/nmeth.3593

Full name	Group-DIA
Home page	http://yuanyueli.github.io/group-dia/
Source code	https://github.com/YuanyueLi/group-dia
Programming language	C++
Authors	Yuanyue Li et al.
Lab & Company	Han Lab
Publication date	2015 Oct.
Analysis strategies	Spectra reconstruction; library-based search

Function:

spectra reconstruction

Pre-processing	Cross-run spectra alignment
Ion grouping criteria	k-means-based precursor-fragment clustering
Fragment assignment	One-to-one and high precursor-fragment correlation-first

MSPLIT-DIA

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Reference:

[18]

MSPLIT-DIA: sensitive peptide identification for data-independent acquisition. 10.1038/nmeth.3655

Full name	MSPLIT-DIA
Home page	http://proteomics.ucsd.edu/software-tools/msplit-dia
Source code	/
Programming language	Java
Authors	Jian Wang et al.
Lab & Company	Bandeira Lab
Publication date	2015 Nov.
Analysis strategies	Library-based search

Function:

Library-based search

Analysis approach	Spectrum-first
SSM score	Cosine similarity
Used prior information	Fragmentation pattern; (optional) RT
Peak-picking of shared m/z	High quality-first by SSM similarity

PECAN (Walnut)

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Reference:

[19]

PECAN: library-free peptide detection for data-independent acquisition tandem mass spectrometry data. 10.1038/nmeth.4390

Full name	PECAN (Walnut in Encyclopedia platform)
Home page	Walnut: https://bitbucket.org/searleb/encyclopedia/wiki/Home; PECAN: https://bitbucket.org/maccosslab/pecan/wiki/Home
Source code	Walnut: https://bitbucket.org/searleb/encyclopedia/src; PECAN: https://bitbucket.org/maccosslab/pecan/src
Programming language	Walnut: Java; PECAN: Python
Authors	Ying S. Ting et al. (re-implemented by Brian C. Searle in Encyclopedia platform)
Lab & Company	MacCoss Lab
Publication date	2017 Aug.
Analysis strategies	Sequence-based search

Function:

Sequence-based search

Analysis approach	Spectrum-first
SSM score	Background score-subtracted dot product
Matching restriction	Reduce fragment matching importance based on frequency

Specter

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Reference:

[20]

Specter: linear deconvolution for targeted analysis of data-independent acquisition mass spectrometry proteomics. 10.1038/nmeth.4643

Full name	Specter
Home page	https://github.com/rpeckner-broad/Specter
Source code	https://github.com/rpeckner-broad/Specter
Programming language	Python
Authors	Ryan Peckner et al.
Lab & Company	Jaffe Lab
Publication date	2018 Apr.
Analysis strategies	Library-based search

Function:

Library-based search

Analysis approach	Spectrum-first
SSM score	Coefficients of linear combination of library spectra
Used prior information	Fragmentation pattern; RT

EncyclopeDIA

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Reference:

[21]

Chromatogram libraries improve peptide detection and quantification by data independent acquisition mass spectrometry. 10.1038/s41467-018-07454-w

[22]

Generating high quality libraries for DIA MS with empirically corrected peptide predictions. 10.1038/s41467-020-15346-1

Full name	EncyclopeDIA
Home page	https://bitbucket.org/searleb/encyclopedia/wiki/Home
Source code	https://bitbucket.org/searleb/encyclopedia/src
Programming language	Java
Authors	Brian C. Searle et al.
Lab & Company	MacCoss Lab & Searle Lab
Publication date	2018 Dec.
Analysis strategies	Library-based search

Function:

Library-based search

Analysis approach	Spectrum-first
SSM score	product of summed correlation-weighted dot products and the factorial of the number of matched ions
Used prior information	Fragmentation pattern; RT

DeepNovo-DIA

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Reference:

[23]

Deep learning enables de novo peptide sequencing from data-independent-acquisition mass spectrometry. 10.1038/s41592-018-0260-3

Full name	DeepNovo-DIA
Home page	https://github.com/nh2tran/DeepNovo-DIA
Source code	https://github.com/nh2tran/DeepNovo-DIA
Programming language	Python
Authors	Ngoc Hieu Tran et al.
Lab & Company	Li Lab
Publication date	2018 Dec.
Analysis strategies	De novo sequencing

PEAKS

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Reference:

[24]

PEAKS: powerful software for peptide de novo sequencing by tandem mass spectrometry. 10.1002/rcm.1196

[25]

A streamlined platform for analyzing tera-scale DDA and DIA mass spectrometry data enables highly sensitive immunopeptidomics. 10.1038/s41467-022-30867-7

Full name	PEAKS
Home page	https://www.bioinfor.com/peaks-software
Authors	Bin Ma et al.
Lab & Company	Bioinformatics Solutions Inc
Support date	2018
Analysis strategies	Sequence-based search; library-based search; de novo sequencing

DIA-NN

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Reference:

Original:

[26]

DIA-NN: neural networks and interference correction enable deep proteome coverage in high throughput. 2020. 10.1038/s41592-019-0638-x

Introduced new analysis strategies for identification, scoring, and quantification of Scanning SWATH data:

[27]

Ultra-fast proteomics with Scanning SWATH. 2021. 10.1038/s41587-021-00860-4

Introduced the PTM scoring function with ubiquitinome DIA data as examples:

[28]

Time-resolved in vivo ubiquitinome profiling by DIA-MS reveals USP7 targets on a proteome-wide scale. 2021. 10.1038/s41467-021-25454-1

Introduced the integration of DIA-NN with FragPipe platform, and the analysis details for diaPASEF data:

[29]

dia-PASEF data analysis using FragPipe and DIA-NN for deep proteomics of low sample amounts. 2022. 10.1038/s41467-022-31492-0

Introduced new analysis strategies for identification, scoring, and quantification of plexDIA data (non-isobaric label):

[30]

Increasing the throughput of sensitive proteomics by plexDIA. 2023. 10.1038/s41587-022-01389-w

Introduced QuantUMS for improved quantification:

[31]

QuantUMS: uncertainty minimisation enables confident quantification in proteomics. 2023. 10.1101/2023.06.20.545604

Full name	DIA-NN
Home page	https://github.com/vdemichev/diann
Source code	https://github.com/vdemichev/diann
Programming language	C++
Authors	Vadim Demichev et al.
Lab & Company	Ralser Lab & Demichev Lab
Publication date	2019 Nov.
Analysis strategies	Library-based search

Function:

Library-based search

Analysis approach	Chromatogram-first
Minimum scoring unit	One best peak
Scoring model	linear classifier and fully-connected neural network

DIA tensor

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Reference:

[32]

Phenotype Classification using Proteome Data in a Data-Independent Acquisition Tensor Format. 2020. 10.1021/jasms.0c00254

Full name	DIA tensor
Home page	https://github.com/guomics-lab/DIAtensor
Source code	https://github.com/guomics-lab/DIAtensor
Programming language	Python
Authors	Fangfei Zhang et al.
Lab & Company	Guo Lab
Publication date	2020 Oct.
Analysis strategies	Sequencing-independent

MaxDIA

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Reference:

[33]

MaxDIA enables library-based and library-free data-independent acquisition proteomics. 2021. 10.1038/s41587-021-00968-7

Full name	MaxDIA
Home page	https://maxquant.org/
Programming language	C#
Authors	Pavel Sinitcyn et al.
Lab & Company	Cox Lab
Publication date	2021 July
Analysis strategies	Library-based search

Function:

Library-based search

Analysis approach	Chromatogram-first
Minimum scoring unit	Peak group
Scoring model	XGBoost

DIAmeter

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Reference:

[34]

DIAmeter: matching peptides to data-independent acquisition mass spectrometry data. 2021. 10.1093/bioinformatics/btab284

Full name	DIAmeter
Home page	http://crux.ms/
Source code	https://github.com/crux-toolkit/crux-toolkit
Programming language	C++
Authors	Yang Young Lu et al.
Lab & Company	Noble Lab
Publication date	2021 July
Analysis strategies	Sequence-based search

Function:

Sequence-based search

Analysis approach	Spectrum-first
SSM score	XCorr
Matching restriction	Maximum PSMs per charge state per spectrum; 2. PSM reduction based on combined sub-scores compared to PSM with highest primary score

FIGS

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Reference:

[35]

FIGS: Featured Ion-Guided Stoichiometry for Data-Independent Proteomics through Dynamic Deconvolution. 10.1021/acs.jproteome.1c00438

Full name	FIGS
Home page	https://github.com/FangYan-USTC/FIGS
Source code	https://github.com/FangYan-USTC/FIGS
Programming language	Python
Authors	Yan Fang et al.
Lab & Company	Zeng Lab
Publication date	2021 July
Analysis strategies	Library-based search

Function:

Library-based search

Analysis approach	Spectrum-first
SSM score	Coefficients of linear combination of library spectra
Used prior information	Fragmentation pattern; RT

mstc

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Reference:

[36]

On the feasibility of deep learning applications using raw mass spectrometry data. 2021. 10.1093/bioinformatics/btab311

Full name	mass_spec_trans_coding
Home page	https://github.com/PhosphorylatedRabbits/mass_spec_trans_coding
Source code	https://github.com/PhosphorylatedRabbits/mass_spec_trans_coding
Programming language	Python
Authors	Joris Cadow et al.
Lab & Company	Martínez Lab
Publication date	2021 July
Analysis strategies	Sequencing-independent

CsoDIAq

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Reference:

[37]

CsoDIAq Software for Direct Infusion Shotgun Proteome Analysis. 10.1021/acs.analchem.1c02021

Full name	CsoDIAq
Home page	https://github.com/CCranney/CsoDIAq
Source code	https://github.com/CCranney/CsoDIAq
Programming language	Python
Authors	Caleb W. Cranney and Jesse G. Meyer
Lab & Company	Meyer Lab
Publication date	2021 Sep.
Analysis strategies	Library-based search

Function:

Library-based search

Analysis approach	Spectrum-first
SSM score	Cosine similarity
Used prior information	Fragmentation pattern

DreamDIA^XMBD

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Reference:

[38]

Deep representation features from DreamDIA^XMBD improve the analysis of data-independent acquisition proteomics. 2021. 10.1038/s42003-021-02726-6

Full name	DreamDIAXMBD
Home page	https://github.com/xmuyulab/DreamDIA-XMBD
Source code	https://github.com/xmuyulab/DreamDIA-XMBD
Programming language	Python
Authors	Mingxuan Gao et al.
Lab & Company	Han Lab & Yu Lab
Publication date	2021 Oct.
Analysis strategies	Library-based search

Function:

Library-based search

Analysis approach	Chromatogram-first
Minimum scoring unit	Raw XICs
Scoring model	LSTM neural network and XGBoost

Dear-DIA^XMBD

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Reference:

[39]

Dear-DIA^XMBD: Deep Autoencoder Enables Deconvolution of Data-Independent Acquisition Proteomics. 2023. 10.34133/research.0179

Full name	Dear-DIAXMBD
Home page	https://github.com/jianweishuai/Dear-DIA-XMBD
Source code	/
Programming language	C++
Authors	Qingzu He et al.
Lab & Company	Jianwei Shuai Lab & Jiahuai Han Lab
Publication date	2023 June
Analysis strategies	Spectra reconstruction

Function:

spectra reconstruction

Pre-processing	Latent representation extraction of fragment XICs via a VAE model
Ion grouping criteria	k-means-based fragment representation clustering and CNN calculated fragment peak group similarity
Fragment assignment	One-to-One

MSFragger-DIA

back to table

Reference:

[40]

Analysis of DIA proteomics data using MSFragger-DIA and FragPipe computational platform. 2023. 10.1038/s41467-023-39869-5

Full name	MSFragger-DIA
Home page	https://msfragger.nesvilab.org & https://github.com/Nesvilab/MSFragger
Programming language	Java
Authors	Fengchao Yu et al.
Lab & Company	Nesvizhskii Lab
Publication date	2023 July (function available in 2020)
Analysis strategies	Sequence-based search

Function:

Sequence-based search

Analysis approach	Spectrum-first
SSM score	MSFragger hyperscore
Matching restriction	Maximum PSMs per spectrum; 2. High PSM score-first signal picking