MSIWarp : A General Approach to Mass Alignment in Mass Spectrometry Imaging
Eriksson, Jonatan O. LU ; Sánchez Brotons, Alejandro ; Rezeli, Melinda LU
; Suits, Frank
; Markó-Varga, György
LU
and Horvatovich, Peter
LU
(2020)
In Analytical Chemistry
92(24).
p.16138-16148
- Abstract
Mass spectrometry imaging (MSI) is a technique that provides comprehensive molecular information with high spatial resolution from tissue. Today, there is a strong push toward sharing data sets through public repositories in many research fields where MSI is commonly applied; yet, there is no standardized protocol for analyzing these data sets in a reproducible manner. Shifts in the mass-to-charge ratio (m/z) of molecular peaks present a major obstacle that can make it impossible to distinguish one compound from another. Here, we present a label-free m/z alignment approach that is compatible with multiple instrument types and makes no assumptions on the sample's molecular composition. Our approach, MSIWarp... (More)
Mass spectrometry imaging (MSI) is a technique that provides comprehensive molecular information with high spatial resolution from tissue. Today, there is a strong push toward sharing data sets through public repositories in many research fields where MSI is commonly applied; yet, there is no standardized protocol for analyzing these data sets in a reproducible manner. Shifts in the mass-to-charge ratio (m/z) of molecular peaks present a major obstacle that can make it impossible to distinguish one compound from another. Here, we present a label-free m/z alignment approach that is compatible with multiple instrument types and makes no assumptions on the sample's molecular composition. Our approach, MSIWarp (https://github.com/horvatovichlab/MSIWarp), finds an m/z recalibration function by maximizing a similarity score that considers both the intensity and m/z position of peaks matched between two spectra. MSIWarp requires only centroid spectra to find the recalibration function and is thereby readily applicable to almost any MSI data set. To deal with particularly misaligned or peak-sparse spectra, we provide an option to detect and exclude spurious peak matches with a tailored random sample consensus (RANSAC) procedure. We evaluate our approach with four publicly available data sets from both time-of-flight (TOF) and Orbitrap instruments and demonstrate up to 88% improvement in m/z alignment.
(Less)
- author
- Eriksson, Jonatan O.
LU
; Sánchez Brotons, Alejandro
; Rezeli, Melinda
LU
; Suits, Frank
; Markó-Varga, György
LU
and Horvatovich, Peter
LU
- organization
- publishing date
- 2020
- type
- Contribution to journal
- publication status
- published
- subject
- in
- Analytical Chemistry
- volume
- 92
- issue
- 24
- pages
- 16138 - 16148
- publisher
- The American Chemical Society (ACS)
- external identifiers
-
- scopus:85097851136
- pmid:33317272
- ISSN
- 0003-2700
- DOI
- 10.1021/acs.analchem.0c03833
- language
- English
- LU publication?
- yes
- id
- 3eb98788-0223-4ba9-9e43-e85b281af822
- date added to LUP
- 2021-01-11 11:30:02
- date last changed
- 2024-06-27 05:56:33
@article{3eb98788-0223-4ba9-9e43-e85b281af822,
abstract = {{<p>Mass spectrometry imaging (MSI) is a technique that provides comprehensive molecular information with high spatial resolution from tissue. Today, there is a strong push toward sharing data sets through public repositories in many research fields where MSI is commonly applied; yet, there is no standardized protocol for analyzing these data sets in a reproducible manner. Shifts in the mass-to-charge ratio (m/z) of molecular peaks present a major obstacle that can make it impossible to distinguish one compound from another. Here, we present a label-free m/z alignment approach that is compatible with multiple instrument types and makes no assumptions on the sample's molecular composition. Our approach, MSIWarp (https://github.com/horvatovichlab/MSIWarp), finds an m/z recalibration function by maximizing a similarity score that considers both the intensity and m/z position of peaks matched between two spectra. MSIWarp requires only centroid spectra to find the recalibration function and is thereby readily applicable to almost any MSI data set. To deal with particularly misaligned or peak-sparse spectra, we provide an option to detect and exclude spurious peak matches with a tailored random sample consensus (RANSAC) procedure. We evaluate our approach with four publicly available data sets from both time-of-flight (TOF) and Orbitrap instruments and demonstrate up to 88% improvement in m/z alignment. </p>}},
author = {{Eriksson, Jonatan O. and Sánchez Brotons, Alejandro and Rezeli, Melinda and Suits, Frank and Markó-Varga, György and Horvatovich, Peter}},
issn = {{0003-2700}},
language = {{eng}},
number = {{24}},
pages = {{16138--16148}},
publisher = {{The American Chemical Society (ACS)}},
series = {{Analytical Chemistry}},
title = {{MSIWarp : A General Approach to Mass Alignment in Mass Spectrometry Imaging}},
url = {{http://dx.doi.org/10.1021/acs.analchem.0c03833}},
doi = {{10.1021/acs.analchem.0c03833}},
volume = {{92}},
year = {{2020}},
}