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 & 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, Metallomics, Volume 14, Issue 3, March 2022, mfac013, https://doi.org/10.1093/mtomcs/mfac013

Python code for LA ICP MS imaging data segmentation

Code & 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 & P. Details on data generation & 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