PXD029694

PXD029694 is an original dataset announced via ProteomeXchange.

Title	Dear-DIA-XMBD applies deep autoencoder to analyze data-independent acquisition data
Description	Although the data-independent acquisition (DIA) technology and the related algorithms are developing rapidly, the results of DIA data analyzing without the use of spectra library from data-dependent acquisition (DDA) data remain unsatisfying. Here we proposed an untargeted analysis method, Dear-DIA-XMBD, for directly analyzing DIA data. Dear-DIA-XMBD first integrates the deep variational autoencoder and triplet loss to learn the representations of extracted ion chromatograms of fragments, then uses the k-means clustering algorithm to aggregate fragments with similar representations into the same classes, and finally establishes the inverted index tables to determine the precursor of fragment cluster between precursors and peptides, and between fragments and peptides. We show that Dear-DIA-XMBD performs superiorly with the highly complicated DIA data of different species obtained by different instrument platforms. We trained the Dear-DIA-XMBD on an Escherichia coli SWATH dataset. We benchmarked the performance of Dear-DIA-XMBD by using the highly complicated sample datasets, which consist of L929 mouse dataset, SWATH-MS Gold Standard (SGS) human dataset (PeptideAtlas PASS00289), HYE124 dataset (PXD002952) with 64 variable windows (TripleTOF 6600).
HostingRepository	iProX
AnnounceDate	2021-11-11
AnnouncementXML	Submission_2021-11-11_19:21:36.431.xml
DigitalObjectIdentifier
ReviewLevel	Peer-reviewed dataset
DatasetOrigin	Original dataset
RepositorySupport	Unsupported dataset by repository
PrimarySubmitter	Qingzu He
SpeciesList	scientific name: Mus musculus; NCBI TaxID: 10090; scientific name: Escherichia coli; NCBI TaxID: 562;
ModificationList	No PTMs are included in the dataset
Instrument	TripleTOF 5600

Revision	Datetime	Status	ChangeLog Entry
0	2021-11-11 19:21:13	ID requested
⏵ 1	2021-11-11 19:21:36	announced

Dataset with its publication pending

submitter keyword: Deep learning, SWATH-DIA

Jianwei Shuai
contact affiliation	Department of Physics, Xiamen University
contact email	jianweishuai@xmu.edu.cn
lab head
Qingzu He
contact affiliation	Department of Physics, Xiamen University
contact email	qingzuhe@stu.xmu.edu.cn
dataset submitter

iProX dataset URI