Data and code for publication: A simple preparation protocol for shipping and storage of tissue sections for laser ablation-inductively coupled plasma-mass spectrometry imaging

Data &amp; Code release for publication: Rebecca Buchholz, Sebastian Krossa, Maria K Andersen, Michael Holtkamp, Michael Sperling, Uwe Karst, May-Britt Tessem, A simple preparation protocol for shipping and storage of tissue sections for laser ablation-inductively coupled plasma-mass spectrometry imaging, <em>Metallomics</em>, Volume 14, Issue 3, March 2022, mfac013, https://doi.org/10.1093/mtomcs/mfac013 Python code for LA ICP MS imaging data segmentation Code &amp; Data also on github Thresholding based segmentation of LA-ICP-MS imaging data Description src/main.py - run this to process LA ICP MS data in data folder - generates matplotlib.figures - project specific setup src/laicpms_data_handler.py - contains object to import, handle and segment (shimadzu) raw data Dependencies Python 3.8.1 or newer For packages see requirements.txt Data LA-ICP-MS imaging data of human prostate tissue of the elements Zn, Fe &amp; P. Details on data generation &amp; collection in publication. LA-ICP-MS imaging data as plain text files (comma-separated values) Condition 1 = fresh frozen (FF) Condition 2 = room temperature vacuum dried and sealed (RTV) Condition 3 = formalin fixed (FFix) Condition 4 = formalin fixed, paraffin sealed (FFPS) 3 replicate sectioning sets named A, B, C File-naming: LA_Data_CISN1.csv, where I = [1, 2, 3, 4] is indicating the condition used and N = [A, B, C] is indicating the replicate set License Data CC-BY 4.0 - respective LICENSE file in data folder Source code MIT - respective LICENSE file in src folder