Ayat Ismail

This project collects summary information and (visual) characterizations of lung health related polygenic scores and underlying GWAS, based on publicly available data.

Mission: We perform cutting-edge research on data generated by novel biomolecular technologies to address questions in pneumology. Towards this, we use biological high-throughput data, i.e., OMICs data, to gain insights into molecular and phenotypic traits and diseases using computational methods. We combine data, methodology and their applications in pneumology through interdisciplinary collaboration with mathematicians, computer scientists, biologists and physicians.

A file combining all CpG sites from the differentially methylated regions (DMRs) of the control, t0, and t1 groups was generated. This combined file, containing methylation values extracted from the bedgraph files, was then used to create a PCA plot and a single heatmap for all CpG sites across the regions.

Majority direction kmer data files were used for the analysis. e.g: results/analysed_icg/xpore_cdna.all/diffmod_s1-s2/majority_direction_kmer_diffmod.table. which has been renamed to : s1_s2.table as uploaded here.

Conda-based DESeq2 pipeline (R 4.5 + Bioconductor) that renders a Quarto report comparing C3 samples to all others in two commands. Bundle includes DET.yml, DET.sh, and DE_C3_vs_all.qmd

This Quarto Markdown file performs differential gene expression analysis using DESeq2, followed by pathway enrichment analysis for Gene Ontology (GO) and KEGG pathways. It includes a heatmap of the top differentially expressed genes and results for GO and KEGG pathway analysis, providing insights into the biological processes affected by experimental conditions.

This ZIP archive contains high-quality PDF figures generated from the postprocessing of xPore RNA modification data. These visualizations summarize key findings and trends across experimental conditions, supporting the interpretation of differential RNA modifications. These figures were produced using a Quarto workflow and are intended for use in reports, presentations, or publications.

This ZIP archive contains the output data generated during the postprocessing of xPore RNA modification analysis. It includes filtered count tables, site-level and gene-level summaries, and other intermediate results used for statistical analysis and visualization.

**Contents may include: **

• • • Site-level counts after filtering
• • • k-mer frequency tables
• • • Gene and transcript-level modification summaries
• • • Data used for generating PCA, volcano plots, and heatmaps

This ZIP archive contains 6 input data tables from the xPore RNA modification analysis, organized by experimental conditions. These tables include modification counts and other relevant data used for downstream analysis and visualization.

This archive contains all necessary files to reproduce the postprocessing and analysis pipeline for [ "omics data analysis in VSMCs"]. The workflow includes a Quarto report, a Conda environment specification (omics-vsmc-env), and input data used for the analysis. The environment ensures reproducibility across systems without requiring hardcoded paths.

Included files:

Postprocessing_no_cov_filter.qmd — The main Quarto report for data visualization and results.

renv.lock and renv/ — R environment ...

This Quarto Markdown file contains a step-by-step workflow for analyzing xPore RNA modification data. It includes filtering, statistical analysis, and visualization to identify and explore differences in RNA modifications between samples. The outputs include:

• PCA plots to check sample clustering
• k-mer counts to see sequence patterns
• Volcano plots to show significant changes
• Heatmaps of modification levels
• Other visual summaries to help interpret the results

This workflow makes it easy ...

This report is the result of running a Quarto Markdown file designed for visualizing and analyzing xPore RNA modification data. It provides clear insights into RNA modifications across different experimental conditions, serving as both a visual and analytical reference for the study.

**Key sections include: **

• PCA plots before and after filtering
• Counts of k-mers at different filtering thresholds
• Gene- and transcript-level modification summaries
• Volcano plots for differential modification ...