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ppromprasert/README.md

Patharapa "Candy" Promprasert

Bioinformatics Analyst | Cancer Genomics | Multi-Omics | Computational Biology

Bioinformatics scientist developing reproducible computational workflows for precision oncology across cancer genomics, transcriptomics, single-cell biology, epigenomics, population genomics, and clinical outcomes.

My work focuses on translating high-dimensional cancer datasets into biologically interpretable and statistically defensible results.

Research Areas

  • Cancer genomics and precision oncology
  • Multi-omics integration
  • Epigenomics and DNA methylation
  • Bulk and single-cell transcriptomics
  • Tumor immune microenvironment
  • Population genomics and genetic ancestry
  • Statistical genomics and survival analysis

Selected Projects

Thyroid Cancer Multi-Omics

Integrated somatic DNA, bulk RNA-seq, clinical phenotypes, molecular drivers, and disease-status information to characterize molecular heterogeneity in thyroid cancer.

Methods: GATK Mutect2, MAF harmonization, somatic-driver reconciliation, DESeq2, PCA, transcriptional program scoring, inflammasome analysis, pathway-level interpretation, multivariable modeling, and DNA–RNA integration.

CMS4 Single-Cell Immune States & Ancestry

Single-cell analysis of ancestry-associated immune-state heterogeneity within CMS4 colorectal cancer.

Methods: Seurat, compartment-specific QC, Harmony batch integration, Azimuth reference annotation, patient-level pseudobulk aggregation, DESeq2, GO Biological Process GSEA, MSigDB Hallmark GSEA.

Immune programs: CD8 cytotoxic/exhaustion states, CD4/Treg/Tfh states, B-cell/plasma differentiation, M2/TAM programs, mast-cell signaling, and progenitor-like lineage states.

OED → OSCC Epigenomic Progression

Longitudinal Illumina EPIC methylation analysis investigating epigenetic alterations associated with progression from oral epithelial dysplasia to oral squamous cell carcinoma.

Methods: EPIC methylation arrays, beta/M-value modeling, limma, duplicateCorrelation, CpG- and gene-level analysis, baseline-definition sensitivity analyses, delta-beta effect sizes, BH-FDR, candidate-gene analysis, and spatial-transcriptomic integration.

HNSC SLC25A10/SFXN3 Survival Genomics

Evaluated reciprocal metabolic-gene expression states and survival outcomes in HPV-negative head and neck squamous cell carcinoma.

Methods: Kaplan–Meier estimation, log-rank testing, Cox proportional hazards regression, continuous-expression models, interaction testing, subsite-specific sensitivity analysis, and nonlinear modeling.

CRC Immunoepigenomics

Integrated methylation-derived immune composition with LINE-1, CIMP, ATM methylation, clinical variables and environmental context.

Methods: EpiDISH RPC, EPIC methylation, immune deconvolution, Spearman correlation, nonparametric testing, multivariable models.

CMS4 Single-Cell CNV Architecture

Evaluated ancestry-stratified chromosomal instability and clonal heterogeneity in CMS4 colorectal tumors using expression-derived single-cell copy-number profiles.

Methods: scRNA-seq, inferCNV, chromosome- and gene-level CNV summarization, clonal diversity, ancestry-stratified comparisons, BH-FDR, and leave-one-sample-out sensitivity analysis.

CRC Population Genomics & Genetic Ancestry

Developed a population-genomics workflow for genetic ancestry estimation from RNA-derived germline variation in colorectal cancer.

Methods: nf-core/rnavar, GATK HaplotypeCaller, bcftools, PLINK, 1000 Genomes/HGDP reference integration, PCA, supervised and unsupervised ADMIXTURE, cross-validation, missingness sensitivity analysis, and Linux/Slurm HPC.

Additional Projects

CRC Immunoepigenomics — EPIC methylation, EpiDISH immune deconvolution, CD8/TIL analysis, LINE-1, CIMP, ATM methylation, environmental and neighborhood-level variables.

CRC Ancestry Transcriptomics & Immunomics — CMS1–4-stratified DESeq2, ancestry-associated transcriptional programs, continuous AFR gradients, xCell and CIBERSORT immune deconvolution.

CRC Single-Cell Cellular Composition — patient-level immune/stromal composition, genetic ancestry, self-reported race, CMS composition, nonparametric inference and FDR control.

DNA Damage & Repair Transcriptomics — DESeq2, ancestry/disease contrasts, DNA-repair and metabolic programs, ashr shrinkage, GO/KEGG/Reactome enrichment.

Cancer Genomics / Exposure Analyses — somatic variation, mutational signatures, copy-number analysis, methylation-associated environmental exposure signatures, and translational cancer genomics.

Technical Stack

Languages: R · Python · Bash · Linux

Workflow / HPC: Nextflow · nf-core · Slurm · Singularity · Conda · Git · GitHub Actions

Cancer Genomics: GATK · Mutect2 · HaplotypeCaller · Funcotator · bcftools · samtools · VEP · ANNOVAR · maftools · GISTIC2

Bulk Transcriptomics: Salmon · DESeq2 · limma · ashr · clusterProfiler · ReactomePA · MSigDB/GSEA

Single-Cell: Seurat · Harmony · Azimuth · SingleR · Monocle3 · inferCNV · pseudobulk differential expression

Epigenomics: Illumina EPIC · sesame · limma · EpiDISH · methylation deconvolution · beta/M-value modeling

Population Genomics: PLINK · ADMIXTURE · SNPRelate · 1000 Genomes · HGDP · PCA

Tumor Immunology: xCell · CIBERSORT · EpiDISH · immune-state scoring · tumor microenvironment profiling

Statistical Genomics: GLM · Cox proportional hazards · Kaplan–Meier · likelihood-ratio tests · interaction models · nonparametric inference · multiple-testing correction

Pinned Loading

  1. thyroid-cancer-multiomics thyroid-cancer-multiomics Public

    Translational thyroid-cancer bioinformatics integrating somatic drivers, RNA-seq, disease status, pathway programs, inflammasome biology, and DNA–RNA analyses.

    R

  2. oed-oscc-epigenomic-progression oed-oscc-epigenomic-progression Public

    EPIC methylation analysis of OED-to-OSCC progression integrating baseline definitions, limma modeling, CpG effect sizes, candidate genes, spatial transcriptomics, and sensitivity analyses.

    R

  3. cms4-singlecell-cnv-ancestry cms4-singlecell-cnv-ancestry Public

    Single-cell inferCNV analysis of CMS4 colorectal cancer evaluating CNV burden, clonal diversity, chromosome/gene-level architecture, and African-ancestry stratification.

    R

  4. crc-population-genomics-ancestry crc-population-genomics-ancestry Public

    Population-genomics workflow for CRC using RNA-derived germline variants, 1000 Genomes, PLINK PCA, supervised/unsupervised ADMIXTURE, and missingness sensitivity.

    Shell

  5. hnsc-slc25a10-sfxn3-survival hnsc-slc25a10-sfxn3-survival Public

    TCGA HNSC survival bioinformatics evaluating SLC25A10 and SFXN3 with Kaplan–Meier, Cox PH, reciprocal expression states, subsite sensitivity, and nonlinear modeling.

    R

  6. cms4-singlecell-immune-states-ancestry cms4-singlecell-immune-states-ancestry Public

    CMS4 CRC single-cell immune-state analysis integrating Seurat, Harmony, Azimuth, pseudobulk DESeq2, pathway GSEA, and African ancestry.

    R