Shon Kurian George

Spatial Transcriptomics Pipeline Development
Image-based cell profiling (cypro : R package)

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Edinburgh, United Kingdom & Kerala, India · Reachable on Email/LinkedIn · Open to Collaboration

About

MSc-trained bioinformatician shipping reproducible analyses and tools with an interest in providing interactive, easy-to-use tools. Skilled in R, Python, Bash Scripting and building bioinformatic pipelines.

Skills

  • R / Shiny, Python, Bash
  • Spatial transcriptomics (SPATA2, Seurat)
  • Version Control & Containerisation (Docker, Git, GitHub)

Interactive applications

SPATA2 Shiny App

R Shiny app that was developed to enable seamless & automated heatmap generation and dataset comparisons by reducing the manual processing time between datasets and making the comparison of the parameters of a specific dataset instantaneous.

Launch app

Protein Conservation & Motif Suite (Python)

Developed a Python script with a terminal interface to query a taxonomic group and retrieve protein sequences via EDirect. Built a workflow integrating NCBI and EMBOSS tools to assemble datasets (up to 1,000 sequences), automate alignments, generate customisable conservation plots, and perform motif discovery.

Launch app

Projects

cypro R package

R package that is aimed at streamlining image-based cell profiling workflows by integrating data from diverse platforms like CellProfiler and CellTracker hosted on GitHub for version control and easy accessibility. Built on the powerful shiny package. Intuitive UI experience where the user is guided through the analysis

View GithHub repo

Spatial Transcriptomics miRNA pipeline

Analysed 10x Visium Spatial Transcriptomics datasets to identify expression patterns of 5 tissue-specific microRNAs (miRNAs) across 8 datasets & 3 major tissue types (brain, heart, liver) at cell-type boundaries.

View GithHub repo

Detailed Collaborative Machine Learning Project on Modifiable Risk Factors Linked to Dementia

Using a Machine Learning pipeline, leveraged the SHARE dataset to identify key modifiable dementia risk factors—highlighting physical activity and social engagement as primary predictors.

Read the report

Analysis and Critique of Automeris io moth de novo Genome Assembly and Annotation by Skojec et al. and assembly using wtdbg2.

Executed a critical evaluation of the genome assembly workflow performed by Skojec et al. and compared assembly quality between Hifiasm (N50: 15.78 Mb) and wtdbg2 (N50: 1.1 Mb). Demonstrated the superior performance of Hifiasm with 98.4% completeness and a 490 Mb assembly across only 600 contigs (vs 3,362).

Read the analysis