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Correcting mass shifts: A lock mass-free recalibration procedure for mass spectrometry imaging data

Overview of attention for article published in Analytical & Bioanalytical Chemistry, September 2015
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  • Above-average Attention Score compared to outputs of the same age and source (63rd percentile)

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Title
Correcting mass shifts: A lock mass-free recalibration procedure for mass spectrometry imaging data
Published in
Analytical & Bioanalytical Chemistry, September 2015
DOI 10.1007/s00216-015-8935-4
Pubmed ID
Authors

Purva Kulkarni, Filip Kaftan, Philipp Kynast, Aleš Svatoš, Sebastian Böcker

Abstract

Mass spectrometry imaging (MSI) has become widely popular because of its potential to map the spatial distribution of thousands of compounds in a single measurement directly from tissue surfaces. With every MSI experiment, it is important to maintain high mass accuracy for correct identification of the observed ions. Many times this can be compromised due to different experimental factors, leading to erroneous assignment of peaks. This makes recalibration a crucial preprocessing step. We describe a lock mass-free mass spectra recalibration method, which enables to significantly reduce these mass shift effects. The recalibration method is applied in three steps: First, we decide on an order to process all the spectra. Herein, we describe three different methods for ordering the spectra-minimum spanning tree (MST), topological greedy (TG), and crystal growth (CG). Second, we construct a reference (consensus) spectrum, from the ordered spectra, and third, all spectra are individually corrected against this consensus spectrum. The performance of the recalibration method is demonstrated on three imaging datasets acquired from matrix-assisted laser desorptionionization (MALDI) and laser desorption/ionization (LDI) mass spectrometry imaging of whole-body Drosophila melanogaster fly. The applied recalibration method is shown to strongly reduce the observed mass shifts in the imaging datasets. Among the three ordering methods, CG and MST perform comparatively better than TG and highly decrease the overall standard deviation of the mass error distribution. Lock mass correction of MSI data is practically difficult, as not all spectra contain the selected lock mass peak. Our method eliminates this need.

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Mendeley readers

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The data shown below were compiled from readership statistics for 36 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Brazil 1 3%
Unknown 35 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 10 28%
Researcher 9 25%
Other 3 8%
Student > Bachelor 2 6%
Student > Doctoral Student 2 6%
Other 3 8%
Unknown 7 19%
Readers by discipline Count As %
Chemistry 10 28%
Biochemistry, Genetics and Molecular Biology 6 17%
Agricultural and Biological Sciences 6 17%
Computer Science 3 8%
Environmental Science 2 6%
Other 3 8%
Unknown 6 17%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 30 September 2015.
All research outputs
#19,945,185
of 25,374,917 outputs
Outputs from Analytical & Bioanalytical Chemistry
#6,060
of 9,619 outputs
Outputs of similar age
#191,128
of 278,999 outputs
Outputs of similar age from Analytical & Bioanalytical Chemistry
#55
of 165 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. This one is in the 18th percentile – i.e., 18% of other outputs scored the same or lower than it.
So far Altmetric has tracked 9,619 research outputs from this source. They receive a mean Attention Score of 3.1. This one is in the 31st percentile – i.e., 31% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 278,999 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 26th percentile – i.e., 26% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 165 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 63% of its contemporaries.