Utilizing Skyline to analyze lipidomics data containing liquid chromatography, ion mobility spectrometry and mass spectrometry dimensions

Kaylie I. Kirkwood, Brian S. Pratt, Nicholas Shulman, Kaipo Tamura, Michael J. MacCoss, Brendan X. MacLean, Erin S. Baker

Published: 2022-07-12 DOI: 10.1038/s41596-022-00714-6

Lipidomics

Skyline

LC-IMS-CID-MS

Data annotation

Open-source software

AI 解读

Supplementary information

Supplementary Information

Supplementary Methods, Supplementary Tables 3–5 and Supplementary Figs. 1–17.

Supplementary Table 1

Transition lists

Supplementary Table 2

iRT prediction results

Preparation of single-cell suspensions of mouse glomeruli for high-throughput analysis

cfSNV: a software tool for the sensitive detection of somatic mutations from cell-free DNA

Anaerobic cryoEM protocols for air-sensitive nitrogenase proteins

Engineering megabase-sized genomic deletions with MACHETE (Molecular Alteration of Chromosomes with Engineered Tandem Elements)

Genome-wide pooled CRISPR screening in neurospheres

Neural cell isolation from adult macaques for high-throughput analyses and neurosphere cultures

Design and fabrication of wearable electronic textiles using twisted fiber-based threads

Nacre-inspired underwater superoleophobic films with high transparency and mechanical robustness

Quantification of organelle contact sites by split-GFP-based contact site sensors (SPLICS) in living cells

Scanorama: integrating large and diverse single-cell transcriptomic datasets

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Figures

References

Supplementary information

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Kirkwood, K. I. et al. Utilizing Skyline to analyze lipidomics data containing liquid chromatography, ion mobility spectrometry and mass spectrometry dimensions. Zenodo https://zenodo.org/record/6374209#.YpzYhBPMJJU (2022).

Utilizing Skyline to analyze lipidomics data containing liquid chromatography, ion mobility spectrometry and mass spectrometry dimensions

Supplementary information

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