01 / Data
Many modalities…one statistical treatment
The assays themselves determine how features are counted. Once the data are tallied, it is largely the same analytical problem — protein, spatial, RNA, and DNA simply reduce to a feature-by-sample matrix. This is how one person can cover so much of this range by themselves. Our team has decades of experience across the vast breadth of what bioinformatic analyses mean.
The deepest area
- Transcriptomics
- Bulk and single-cell RNA, whole cell or nuclei.
- Chromatin
- Bulk ATAC, single-nuclei ATAC, and paired multiome.
- Genomes
- Exome, whole genome, targeted panels, structural rearrangement.
- Populations
- Genome-wide SNPs, microsatellites, population structure.
- Microbial communities
- Metagenomics, microbiome and antimicrobial resistome.
- Repertoire
- T-cell receptor sequencing, small RNA.
- Proteomics
- Differential abundance, normalization, and analysis
- Metabolomics
- The same framework over a different feature space.
- Multi-omic integration via AI
- Several platforms on one cohort, analyzed together through AI incorporation.
Spatial and in-situ
- Xenium
- In-situ transcriptomics at single-cell resolution.
- Atera
- 10x's newer in-situ platform, analyzed on the same footing.
Independent of platform
- Design and power
- What a study can detect, decided before it runs rather than defended afterwards.
- Modeling
- Mixed models, repeated measures, and the choice of replication unit — often what decides whether a result survives review.
02 / Systems
Statistics does not care what the organism is
Which has been fortunate, because the questions have arrived from almost everywhere. Every organism below is named in the bibliography — 124 of them, across 25 taxonomic classes and all four domains of life, from human trauma patients to hot-spring archaea. The first publication was a logistic regression for zoo neonate management in 1995, and the range has widened every year since.
Two papers are worth singling out for scale: five hundred microsatellite loci developed for Peromyscus, and a marker-development method validated across thirty-two species at once. Where a paper covered a community rather than a species — prairie soil, the beef resistome — it is counted once, so the true species total is higher than the number above.
03 / Fields
27 fields of study, and counting
The constant is the statistics. The biology has been whatever walked through the door.
Biomedical
- Trauma and transfusion medicine
- Oncology, adult and paediatric
- Cardiology
- Craniofacial development
- Immunology
- Diabetes and metabolism
- Ophthalmology
- Nephrology
- Neuroscience and ageing
- Dermatology
- Rheumatology
- Haematology
- Reproductive medicine
- Obesity and exercise physiology
- Virology
- Infectious disease
- Toxicology
Environmental and agricultural
- Conservation genetics
- Wildlife management
- Fisheries and aquaculture
- Soil and microbial ecology
- Food safety
- Antimicrobial resistance
- Plant science
- Entomology
- Herpetology
- Ornithology
04 / Record
Published work
244 publications, 1995–2026
Thirty-one years of being the person other laboratories bring their data to. The first entry is a logistic regression for managing zoo neonates; the most recent is multiomic endotyping of trauma patients in Science Translational Medicine. In between: whooping crane studbooks, prairie soil fungi, dilated cardiomyopathy genetics, paediatric glioma, and the antimicrobial resistome of the beef production chain.
Consortium and resource work included — FaceBase, and the MEGARes antimicrobial resistance database.
05 / Software
Open source
The analysis framework behind much of the sequence-based work is released publicly.
Paralome
A reproducible, checkpointed workflow framework for omics analysis on HPC — one backbone under independent RNA, ATAC and variant pipelines.
Read about Paralome →06 / Contact
Ken Jones
Ken.Jones@bioinformaticsolutions.com