Ms2lda.org: web-based topic modelling for substructure discovery in mass spectrometry

被引：81

作者：

Wandy, Joe ^{[1
]}

Zhu, Yunfeng ^{[2
]}

van der Hooft, Justin J. J. ^{[1
]}

Daly, Ronan ^{[1
]}

Barrett, Michael P. ^{[1
,2
]}

Rogers, Simon ^{[3
]}

机构：

[1] Glasgow Poly Univ Glasgow, Glasgow, Lanark, Scotland

[2] Wellcome Ctr Mol Parasitol, Glasgow, Lanark, Scotland

[3] Univ Glasgow, Sch Comp Sci, Glasgow, Lanark, Scotland

来源：

BIOINFORMATICS | 2018年 / 34卷 / 02期

基金：

英国惠康基金; 英国生物技术与生命科学研究理事会;

关键词：

D O I：

10.1093/bioinformatics/btx582

中图分类号：

Q5 [生物化学];

学科分类号：

071010 ; 081704 ;

摘要：

Motivation: We recently published MS2LDA, a method for the decomposition of sets of molecular fragment data derived from large metabolomics experiments. To make the method more widely available to the community, here we present ms2lda.org, a web application that allows users to upload their data, run MS2LDA analyses and explore the results through interactive visualizations. Results: Ms2lda.org takes tandem mass spectrometry data in many standard formats and allows the user to infer the sets of fragment and neutral loss features that co-occur together (Mass2Motifs). As an alternative workflow, the user can also decompose a data set onto predefined Mass2Motifs. This is accomplished through the web interface or programmatically from our web service.

引用

页码：317 / 318

页数：2

共 2 条

[1] Pathway level analysis of gene expression using singular value decomposition [J].