<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Eriksson JO</submitter><funding>Fru Berta Kamprads Stiftelse</funding><funding>Dutch Research Council (NWO)</funding><pagination>16138-16148</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC7745203</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>92(24)</volume><pubmed_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 (&lt;i>m&lt;/i>/&lt;i>z&lt;/i>) of molecular peaks present a major obstacle that can make it impossible to distinguish one compound from another. Here, we present a label-free &lt;i>m&lt;/i>/&lt;i>z&lt;/i> 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 &lt;i</pubmed_abstract><journal>Analytical chemistry</journal><pubmed_title>MSIWarp: A General Approach to Mass Alignment in Mass Spectrometry Imaging.</pubmed_title><pmcid>PMC7745203</pmcid><funding_grant_id>184.034.019</funding_grant_id><pubmed_authors>Marko-Varga G</pubmed_authors><pubmed_authors>Suits F</pubmed_authors><pubmed_authors>Eriksson JO</pubmed_authors><pubmed_authors>Horvatovich P</pubmed_authors><pubmed_authors>Sanchez Brotons A</pubmed_authors><pubmed_authors>Rezeli M</pubmed_authors></additional><is_claimable>false</is_claimable><name>MSIWarp: A General Approach to Mass Alignment in Mass Spectrometry Imaging.</name><description>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 (&lt;i>m&lt;/i>/&lt;i>z&lt;/i>) of molecular peaks present a major obstacle that can make it impossible to distinguish one compound from another. Here, we present a label-free &lt;i>m&lt;/i>/&lt;i>z&lt;/i> 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 &lt;i</description><dates><release>2020-01-01T00:00:00Z</release><publication>2020 Dec</publication><modification>2025-04-26T09:09:06.641Z</modification><creation>2025-04-06T12:56:16.218Z</creation></dates><accession>S-EPMC7745203</accession><cross_references><pubmed>33317272</pubmed><doi>10.1021/acs.analchem.0c03833</doi></cross_references></HashMap>