Skip to content

Releases: Power-Quant/pGlycoQuant

pQuant/pGlycoQuant_v202401

08 Jan 11:48
f6ac8df

Choose a tag to compare

Version Information

  • Version: pQuant/pGlycoQuant_v202401 (pQuant-pGlycoQuant_v202401)

  • Release Date: 2024.01.04

  • In the current version, we updated the license.

Cite us

Kong, S., Gong, P., Zeng, WF. et al. pGlycoQuant with a deep residual network for quantitative glycoproteomics at intact glycopeptide level. Nat Commun 13, 7539 (2022).

doi: https://doi.org/10.1038/s41467-022-35172-x

Contact us

Please send email to pglycoquant[at]126.com for more communications! (Please change "[at]" into "@".)

pQuant/GlycoQuant_v202306

03 Jul 10:34
f6ac8df

Choose a tag to compare

Version Information

  • Version: pQuant/pGlycoQuant_v202306 (pQuant-pGlycoQuant_v202306)

  • Release Date: 2023.06.30

  • In the current version, we updated the license.

  • The user manual is the same as last version (v202302).

  • We fixed some bugs on July 11th. If you are unable to run properly, you can download the version again.

Cite us

Kong, S., Gong, P., Zeng, WF. et al. pGlycoQuant with a deep residual network for quantitative glycoproteomics at intact glycopeptide level. Nat Commun 13, 7539 (2022).

doi: https://doi.org/10.1038/s41467-022-35172-x

Contact us

Please send email to pglycoquant[at]126.com for more communications! (Please change "[at]" into "@".)

pQuant/pGlycoQuant_v202302

01 Feb 07:51
f6ac8df

Choose a tag to compare

Version Information

  • Version: pQuant/pGlycoQuant_v202302 (pQuant-pGlycoQuant_v202302)

  • Release Date: 2023.02.01

  • In the current version, we fixed some bugs during glyco-quantitation when using MIR, and fixed the quantitation results analysis for N-glyco (Quant.glycan_occupancy.list and Quant.site_occupancy.list) and O-glyco (no analysis results).

  • We updated the User Interface.

Cite us

Kong, S., Gong, P., Zeng, WF. et al. pGlycoQuant with a deep residual network for quantitative glycoproteomics at intact glycopeptide level. Nat Commun 13, 7539 (2022).

doi: https://doi.org/10.1038/s41467-022-35172-x

zendo: 10.5281/zenodo.7267831

Contact us

Please send email to pglycoquant[at]126.com for more communications! (Please change "[at]" into "@".)

Full Changelog: pGlycoQuant_v20220920...pQuant/pGlycoQuant_v202302

pQuant/pGlycoQuant_v202301

03 Jan 09:37
f6ac8df

Choose a tag to compare

Version Information

  • Version: pQuant/pGlycoQuant_v202301 (pQuant-pGlycoQuant_v202301)

  • Release Date: 2023.01.03

  • In the current version, from the perspective of software engineering, in order to facilitate later software maintenance and version update, we combine pQuant and pGlycoQuant into one engineering software. In order to unify, the display information and result files output by the software will be named [Quant], Quant.protein.list, Quant.spectra.list and so on. You can double-click pQuantUI.exe or pGlycoQuantUI.exe to run pQuant or pGlycoQuant separately.

  • In addition, we have improved the efficiency of quantitative measurement by building a library for pFind identification results.

  • Some more concise and convenient functions have been added to the interface.

Cite us

Kong, S., Gong, P., Zeng, WF. et al. pGlycoQuant with a deep residual network for quantitative glycoproteomics at intact glycopeptide level. Nat Commun 13, 7539 (2022).

doi: https://doi.org/10.1038/s41467-022-35172-x

zendo: 10.5281/zenodo.7267831

Contact us

Please send email to pglycoquant[at]126.com for more communications! (Please change "[at]" into "@".)

pQuant/pGlycoQuant_v202212

26 Dec 15:19
f6ac8df

Choose a tag to compare

Version Information

  • Version: pQuant/pGlycoQuant_v202212 (pQuant-pGlycoQuant_v202212)

  • Release Date: 2022.12.26

  • In the current version, from the perspective of software engineering, in order to facilitate later software maintenance and version update, we combine pQuant and pGlycoQuant into one engineering software. In order to unify, the display information and result files output by the software will be named [pQuant], pQuant.protein.list, pQuant.spectra.list and so on.

  • In addition, we have improved the efficiency of quantitative measurement by building a library for pFind identification results.

  • Some more concise and convenient functions have been added to the interface.

Cite us

Kong, S., Gong, P., Zeng, WF. et al. pGlycoQuant with a deep residual network for quantitative glycoproteomics at intact glycopeptide level. Nat Commun 13, 7539 (2022).

doi: https://doi.org/10.1038/s41467-022-35172-x

zendo: 10.5281/zenodo.7267831

Contact us

Please send email to pglycoquant[at]126.com for more communications! (Please change "[at]" into "@".)

pQuant/pGlycoQuant_v202310v2

13 Oct 03:48
f6ac8df

Choose a tag to compare

Pre-release

Version Information

  • Version: pQuant/pGlycoQuant_v202310v2 (pQuant-pGlycoQuant_v202310v2)

  • Release Date: 2023.10.13

  • In the current version, N15 labeling can be used on glycopeptides quantification.

Cite us

Kong, S., Gong, P., Zeng, WF. et al. pGlycoQuant with a deep residual network for quantitative glycoproteomics at intact glycopeptide level. Nat Commun 13, 7539 (2022).

doi: https://doi.org/10.1038/s41467-022-35172-x

Contact us

Please send email to pglycoquant[at]126.com for more communications! (Please change "[at]" into "@".)

pQuant/pGlycoQuant_v202310

12 Oct 14:45
f6ac8df

Choose a tag to compare

Pre-release

Version Information

  • Version: pQuant/pGlycoQuant_v202310 (pQuant-pGlycoQuant_v202310)

  • Release Date: 2023.10.12

  • In the current version, we change the way to register.

Cite us

Kong, S., Gong, P., Zeng, WF. et al. pGlycoQuant with a deep residual network for quantitative glycoproteomics at intact glycopeptide level. Nat Commun 13, 7539 (2022).

doi: https://doi.org/10.1038/s41467-022-35172-x

Contact us

Please send email to pglycoquant[at]126.com for more communications! (Please change "[at]" into "@".)

pGlycoQuant_v202211

07 Nov 16:47
6c5cb04

Choose a tag to compare

Version Information

  • Version: pGlycoQuant_v202211

  • Release Date: 2022.11.07

  • In this version, some small problems have been fixed.

  • In this version, we extended the permission of the software to 2023.06.30.

Discription

Here, we report pGlycoQuant, a generic software tool for quantitative intact glycopeptide analysis, supporting both primary and tandem mass spectrometry quantitation for multiple quantitative strategies. pGlycoQuant advances in glycopeptide evidence matching through applying a deep learning model that reduces missing values for glycopeptide quantification by over 60% compared with Byologic, MSFragger-Glyco and Skyline, as well as an optional function of Match-In-Run (MIR) algorithm for more quantitative coverage of glycopeptides, thus greatly expanding the quantitative function of several powerful search engines, currently including pGlyco 2.0, pGlyco3, Byonic and MSFragger-Glyco.

Computer configuration

  • RAM: 16G or higher is recommended

  • ROM: for one raw data (1G) 2G or higher is recommended

  • OS: Windows10 or higher

  • Other: MSFileReader 3.0 Sp1 or higher is needed

GUI Operation Usage

Please read "Manual for pGlycoQuant.pdf" to learn the useage of pGlycoQuant.

Cite us

Weiqian Cao, et. al. pGlycoQuant with a deep residual network for precise and minuscule-missing-value quantitative glycoproteomics enabling the functional exploration of site-specific glycosylation. bioRxiv 2021.11.15.468561.

doi: https://doi.org/10.1101/2021.11.15.468561

zendo: 10.5281/zenodo.7267831

Contact us

Please send email to pglycoquant[at]126.com for more communications! (Please change "[at]" into "@".)

pGlycoQuant_v20221031

31 Oct 14:12
6c5cb04

Choose a tag to compare

Version Information

  • Version: pGlycoQuant_v202210

  • Release Date: 2022.10.31

  • In this version, the software will be used until 2022.12.31.

  • In this version, some small problems have been fixed.

Discription

Here, we report pGlycoQuant, a generic software tool for quantitative intact glycopeptide analysis, supporting both primary and tandem mass spectrometry quantitation for multiple quantitative strategies. pGlycoQuant advances in glycopeptide evidence matching through applying a deep learning model that reduces missing values for glycopeptide quantification by over 60% compared with Byologic, MSFragger-Glyco and Skyline, as well as an optional function of Match-In-Run (MIR) algorithm for more quantitative coverage of glycopeptides, thus greatly expanding the quantitative function of several powerful search engines, currently including pGlyco 2.0, pGlyco3, Byonic and MSFragger-Glyco.

Computer configuration

  • RAM: 16G or higher is recommended

  • ROM: for one raw data (1G) 2G or higher is recommended

  • OS: Windows10 or higher

  • Other: MSFileReader 3.0 Sp1 or higher is needed

GUI Operation Usage

Please read "Manual for pGlycoQuant.pdf" to learn the useage of pGlycoQuant.

Cite us

Weiqian Cao, et. al. pGlycoQuant with a deep residual network for precise and minuscule-missing-value quantitative glycoproteomics enabling the functional exploration of site-specific glycosylation. bioRxiv 2021.11.15.468561.

doi: https://doi.org/10.1101/2021.11.15.468561

zendo: 10.5281/zenodo.7267831

pGlycoQuant_v20220920

20 Sep 08:54
6c5cb04

Choose a tag to compare

Version Information

  • Version: pGlycoQuant_v20220920

  • Release Date: 2022.09.20

  • In this version, we fixed a bug when the identification result contains RAW or MS files that have not been filled in the pGlycoQuantUI.

  • In this version, the software will be used until 2022.12.31.

Discription

Here, we report pGlycoQuant, a generic software tool for quantitative intact glycopeptide analysis, supporting both primary and tandem mass spectrometry quantitation for multiple quantitative strategies. pGlycoQuant advances in glycopeptide evidence matching through applying a deep learning model that reduces missing values for glycopeptide quantification by over 60% compared with Byologic, MSFragger-Glyco and Skyline, as well as an optional function of Match-In-Run (MIR) algorithm for more quantitative coverage of glycopeptides, thus greatly expanding the quantitative function of several powerful search engines, currently including pGlyco 2.0, pGlyco3, Byonic and MSFragger-Glyco.

Computer configuration

  • RAM: 16G or higher is recommended

  • ROM: for one raw data (1G) 2G or higher is recommended

  • OS: Windows10 or higher

  • Other: MSFileReader 3.0 Sp1 or higher is needed

GUI Operation Usage

Please read "Manual for pGlycoQuant.pdf" to learn the useage of pGlycoQuant.

Cite us

Weiqian Cao, et. al. pGlycoQuant with a deep residual network for precise and minuscule-missing-value quantitative glycoproteomics enabling the functional exploration of site-specific glycosylation. bioRxiv 2021.11.15.468561.

doi: https://doi.org/10.1101/2021.11.15.468561

zendo: 10.5281/zenodo.7267831

Contact us

Please send email to pglycoquant[at]126.com for more communications! (Please change "[at]" into "@".)