A collection of smaller standalone scripts and utilities that do not fit naturally into one of my other repositories or are not large enough to warrant a dedicated repository of their own.
Each utility is kept in its own directory along with a project-specific README containing additional documentation and usage information.
misc/
├── hg38_lib_updater/
│ ├── README.md
│ └── hg38_lib_update.sh
├── random_audio_checker/
│ ├── README.md
│ └── random_audio_check.sh
├── respiratory_pathogen_prevalence/
│ ├── README.md
│ ├── build_estimates.py
│ ├── estimates.csv
│ └── index.html
└── README.md
A Bash utility originally developed to help migrate an internal sequencing library to the hg38 genome build. Given a GSM accession and one or more corresponding SRR accessions, the script can download FASTQ files from GEO or ENA and run them through the ENCODE pipeline.
Although originally written for hg38, it can also work with other configured genome builds such as mm10. The script includes options for retrying downloads, ENA checksum validation, logging, cleanup behavior, LSF job submission, and testing workflows.
See hg38_lib_updater/README.md for full documentation and usage.
A Bash utility that uses ffmpeg to quickly check whether a video file contains audible audio. Instead of processing the entire video, it samples several short sections from randomly selected locations and measures their audio levels.
The number of samples and sample duration can be configured, making it useful for quickly checking long video files without scanning the entire file.
See random_audio_checker/README.md for usage information.
An interactive page showing the estimated share of US upper and lower respiratory tract infections caused by each pathogen (viruses, bacteria, fungi and protozoa) for every year from 2015 to 2026. Each tract has ranked horizontal bars for the selected year and full-width, clickable 100% stacked bars for every year, all sharing one color legend. The table gives estimated illness counts alongside each share.
The numbers are modeled estimates built from CDC surveillance and published etiology studies by build_estimates.py, which also writes every value to estimates.csv.
See respiratory_pathogen_prevalence/README.md for the method, caveats and sources.