This repository contains some of the most substantial Python notebooks I created in my PhD research and used to produce many of the figures found in my thesis.
LA-ICP-MS_image_analysis_and_plotting.ipynb provides the workflow for the analysis and comparison of elemental abundances of Laser Ablation Inductively Coupled Plasma Mass Spectrometry (LA-ICP-MS) metallomic maps as well as the processing and plotting of the maps in flat and log scales to make the figures in Chapter 2 of my thesis. Was also used to produce the animation above - 208Pb distribution in the gut of an earthworm from an abandoned lead mine site.
MRE_candidate_gene_discovery_example.ipynb was used to discover candidate genes that are potentially regulated via the Metal Responsive Element in the genome of Lumbricus rubellus (the 18 chromosomes from NCBI accession: GCA_945859625.1).The script requires a FASTA file with your sequence of interest, and the gene prediction data (gtf file) for that sequence. The output of this code is the Suplementary Table 2; Figures 51-57 were produced using elements of the code found in this script.
The Tetranucleotide_count_rough_workbook.ipynb script was used to count 4-mers in the genome assembly of the earthworm from Cwmystwyth in attempt to remove contaminating reads/contigs. Script requires only the FASTA file with sequences of interest (reads or contigs). This notebook was not tidied up to preserve the figure output for display. Figure 23 was created using this script.
The Whole_chromosome_variant_analysis_example.ipynb script was used to merge the long-read genome assembly (PacBio), gene prediction (FINDER), variant calling (DeepVariant), and annotation (UPIMAPI) datasets, produce statistics from the combined data, and allow visualisation of key loci on chromosomes of Lumbricus rubellus genomes via a Myriapoda plot (example image below). This script served as the cornerstone in production of comparative figures in Chapter 4 of my thesis (example below) and the majority of the statistical tables in Chapter 4.
