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

<p>Data &amp; Code release for publication:</p> <p>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,&nbsp;<em>Metallomics</em>, Volume 14, Issue 3, March 2022, mfac013,&nbsp;<a href="https://doi.org/10.1093/mtomcs/mfac013">https://doi.org/10.1093/mtomcs/mfac013</a></p> <p>Python code for LA ICP MS imaging data segmentation</p> <p>Code &amp; Data also on <a href="https://github.com/sekro/la-icp-msi_segmentation">github</a></p> <p>Thresholding based segmentation of LA-ICP-MS imaging data</p> <p>Description</p> <p><a href="https://github.com/sekro/la-icp-msi_segmentation/blob/master/src/main.py">src/main.py</a>&nbsp;- run this to process LA ICP MS data in data folder - generates matplotlib.figures - project specific setup&nbsp;<a href="https://github.com/sekro/la-icp-msi_segmentation/blob/master/src/laicpms_data_handler.py">src/laicpms_data_handler.py</a>&nbsp;- contains object to import, handle and segment (shimadzu) raw data</p> <p>Dependencies</p> <p>Python 3.8.1 or newer</p> <p>For packages see&nbsp;<a href="https://github.com/sekro/la-icp-msi_segmentation/blob/master/requirements.txt">requirements.txt</a></p> <p>Data</p> <p>LA-ICP-MS imaging data of&nbsp;human prostate tissue of the elements Zn, Fe &amp; P. Details on data generation &amp; collection in <a href="https://doi.org/10.1093/mtomcs/mfac013">publication</a>. LA-ICP-MS imaging data as plain text files (comma-separated values)</p> <ul> <li>Condition 1 = fresh frozen (FF)</li> <li>Condition 2 = room temperature vacuum dried and sealed (RTV)</li> <li>Condition 3 = formalin fixed (FFix)</li> <li>Condition 4 = formalin fixed, paraffin sealed (FFPS)</li> </ul> <p>3 replicate sectioning sets named A, B, C</p> <p>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</p> <p>License</p> <p>Data</p> <p>CC-BY 4.0 - respective&nbsp;<a href="https://github.com/sekro/la-icp-msi_segmentation/blob/master/data/LICENSE">LICENSE</a>&nbsp;file in data folder</p> <p>Source code</p> <p>MIT - respective&nbsp;<a href="https://github.com/sekro/la-icp-msi_segmentation/blob/master/src/LICENSE">LICENSE</a>&nbsp;file in src folder</p>