PALMsiever: A tool to turn raw data into results for single-molecule localization microscopy

Thomas Pengo, Seamus J. Holden, Suliana Manley

Research output: Contribution to journalArticlepeer-review

19 Scopus citations

Abstract

During the past decade, localization microscopy (LM) has transformed into an accessible, commercially available technique for life sciences. However, data processing can be challenging to the non-specialist and care is still needed to produce meaningful results. PALMsiever has been developed to provide a user-friendly means of visualizing, filtering and analyzing LM data. It includes drift correction, clustering, intelligent line profiles, many rendering algorithms and 3D data visualization. It incorporates the main analysis and data processing modalities used by experts in the field, as well as several new features we developed, and makes them broadly accessible. It can easily be extended via plugins and is provided as free of charge open-source software.

Original languageEnglish (US)
Pages (from-to)797-798
Number of pages2
JournalBioinformatics
Volume31
Issue number5
DOIs
StatePublished - Mar 1 2015

Bibliographical note

Funding Information:
TP was supported by the Brazilian Swiss Joint Research Programme of the EPFL and the SystemTB Collaborative Project (Ref. 241587), funded by EU FP7. SH and SM were supported by ERC Starting Grant 243016. SH was supported by a Marie Curie Intra-European Fellowship, PIEF-GA-2011-297918.

Publisher Copyright:
© The Author 2014. Published by Oxford University Press. All rights reserved.

Copyright:
Copyright 2017 Elsevier B.V., All rights reserved.

Fingerprint Dive into the research topics of 'PALMsiever: A tool to turn raw data into results for single-molecule localization microscopy'. Together they form a unique fingerprint.

Cite this