I will analyze single cell rna sequencing scrna seq data

You sequenced your cells. Now you need answers, not a six-month detour into learning Python.

I analyze single-cell RNA-seq data and deliver clear, publication-ready outputs.

What you get: quality control and filtering, cell clustering and cell-type annotation, marker-gene tables, 300-dpi figures, and clear biological interpretation of your results.

Higher tiers can include: differential expression between conditions, cell-composition changes, pathway enrichment, trajectory analysis, cell-cell signaling analysis, manuscript methods text, analysis code, and processed data, where appropriate for your dataset.

Accepted formats: 10x Genomics, .h5ad, .h5, .loom, .csv, and .tsv. Human, mouse, rat, and macaque data.

Why me: I built and run my own single-cell analysis platform using Python, Scanpy, UMAP, and Leiden clustering. Your data goes through a tested scientific workflow, and you receive the figures, tables, and an explanation of what they mean.

Not sure which tier you need? Message me your sample count, conditions, and data format.