Reproducible bioinformatics analysis, auditable workflows, and publication-ready scientific figures.

I am a bioinformatics analyst and doctoral candidate in Integrated Chinese and Western Medicine (Clinical Medicine). I support researchers, laboratories, and academic teams with reproducible bioinformatics analysis and scientific data visualization.

My core capabilities include bulk RNA-seq differential-expression analysis, single-cell RNA-seq analysis, Affymetrix microarray analysis, biostatistics, survival analysis, pathway enrichment, WGCNA, cross-cohort expression validation, immune-infiltration estimation, mutation and research TMB analysis, and public cancer transcriptomics.

Every project begins with validation of the input structure, sample identities, metadata alignment, study design, statistical assumptions, and data quality. Depending on the agreed scope, deliverables may include complete result tables, publication-ready figures, methods and interpretation notes, organized output files, quality-control records, and project-specific R or Python scripts.

I emphasize transparent and auditable work. Methods, software versions, assumptions, sensitivity findings, and limitations are reported clearly. I do not alter scientific results, fabricate evidence, or guarantee statistical significance.

I work only with de-identified and authorized research data. Before a project begins, I review the species, data type and format, study design, intended comparison, expected deliverables, budget, and deadline to confirm feasibility and define a clear scope.

Work Terms

I normally respond to new messages within 24 hours. Before starting, I confirm the project scope, accepted input files, study design, deliverables, milestones, deadline, revision limits, and any work that is explicitly excluded.

Projects are completed through Guru with SafePay or funded milestones. Work begins after the agreed milestone is funded and the required files and metadata have been received.

Clients must provide de-identified, authorized data and accurate sample-mapping information. Raw FASTQ processing, complex longitudinal, nested, multifactor, or interaction designs require a separate feasibility review and quotation.

Revisions cover corrections or reasonable refinements within the agreed scope. New comparisons, additional datasets, new analysis modules, or changes to the study design are treated as additional work.

Project data and unpublished research information are handled confidentially. Final delivery may include organized result tables, figures, reports, quality-control records, and project-specific scripts as defined in the agreement.