Alvarez-Jarreta, Jorge, Rodrigues, Patricia R.S., Fahy, Eoin, O'Connor, Anne, Price, Anna, Gaud, Caroline, Andrews, Simon, Benton, Paul, Siuzdak, Gary, Hawksworth, Jade I., Valdivia-Garcia, Maria, Allen, Stuart M., O'Donnell, Valerie B. and Valencia, Alfonso
2020.
LipidFinder 2.0: advanced informatics pipeline for lipidomics discovery applications.
Bioinformatics
10.1093/bioinformatics/btaa856
![]() |
![]() |
PDF (Creative Commons Attribution License 4.0)
- Accepted Post-Print Version
Download (233kB) |
Abstract
We present LipidFinder 2.0, incorporating four new modules that apply artefact filters, remove lipid and contaminant stacks, in-source fragments and salt clusters, and a new isotope deletion method which is significantly more sensitive than available open-access alternatives. We also incorporate a novel false discovery rate (FDR) method, utilizing a target-decoy strategy, which allows users to assess data quality. A renewed lipid profiling method is introduced which searches three different databases from LIPID MAPS and returns bulk lipid structures only, and a lipid category scatter plot with color blind friendly pallet. An API interface with XCMS Online is made available on LipidFinder’s online version. We show using real data that LipidFinder 2.0 provides a significant improvement over non-lipid metabolite filtering and lipid profiling, compared to available tools.
Item Type: | Article |
---|---|
Date Type: | Published Online |
Status: | In Press |
Schools: | Computer Science & Informatics Medicine |
Publisher: | Oxford University Press |
ISSN: | 1367-4803 |
Funders: | Wellcome Trust |
Date of First Compliant Deposit: | 21 October 2020 |
Date of Acceptance: | 20 September 2020 |
Last Modified: | 05 Nov 2020 14:21 |
URI: | http://orca.cf.ac.uk/id/eprint/135819 |
Actions (repository staff only)
![]() |
Edit Item |