Software
Open, reproducible science
I develop R tools and workflows that connect biological questions to transparent, reproducible analysis.
R / Bioconductor · Version 1.2.0
DspikeIn
Estimating Absolute Abundance from Microbial Spike-in Controls
A modular workflow for absolute microbial quantification using single spike-in taxa or synthetic microbial communities. Supports spike-in validation, preprocessing, scaling-factor estimation, absolute-abundance conversion, bias correction and normalization, with phyloseq and TreeSummarizedExperiment compatibility.
BiocManager::install("DspikeIn")
First time using Bioconductor?
Install BiocManager first with install.packages("BiocManager"), then run the command above.
MIT licence · Package DOI ↗
R / CRAN · Version 1.0.6
HRRI
Diagnostics for Soil–Plant–Microbial Redox Recovery
Integrate longitudinal soil, plant and microbial observations to examine redox disturbance and recovery. Includes recovery signatures, fixed-reference domain scores, observation-coverage diagnostics, and conditional calculations of oxygen demand and accessible electron capacity.
install.packages("HRRI")
R ≥ 4.3.0 · MIT licence · Package DOI ↗
R / GitHub · Version 0.4.19
FmFunMel
From fungal confrontation photographs to matched-control results.
FunMel measures the colour, shape and image-darkness profiles of approximately round Zymoseptoria tritici colonies around another fungus. It separates target colonies from central fungal tissue and connected hyphal growth, preserves image provenance and custom metadata, and compares treatments with their own set controls.
Colony phenotypingMatched controls
install.packages("remotes")
remotes::install_github("mghotbi/FunMel")
Installation requirements
Restart R before loading an updated package. R ≥ 4.1 and source-compilation tools are required: Xcode Command Line Tools on macOS, matching Rtools on Windows, or R development tools and ImageMagick development libraries on Linux. For installed tutorials, use build_vignettes=TRUE during installation.