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tron-mainz/3ddensenet_indel
3ddensenet_indel is a machine learning model from tron-mainz. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as cc-by-nc-nd-4.0.
This is a 3D DenseNet model for detection of somatic indel candidates.
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Updated May 5, 2025
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From the Hugging Face model README
This is a 3D DenseNet model for detection of somatic indel candidates.
Using matched tumor-normal paired short read sequencing data, you can call a list of somatic small indels.
This model is a part of VariantMedium somatic variant caller and is integrated directly into its workflow https://github.com/TRON-Bioinformatics/VariantMedium
The model on its own is not intended to create a final list of variant calls, it is intended a part of a pipeline (https://github.com/TRON-Bioinformatics/VariantMedium)
The model is trained on the output of cell line WES, TCGA WES, and an AML WGS, both originating from short read Illumina sequencing. It is tested for other cancer entities and mostly for solid tumors, but is not tested for non-Illumina sequencing.
We recommend using this model for Illumina-based WES and WGS (paired, short read).
Matched tumor-normal sequencing published under https://ega-archive.org/studies/EGAS00001007633 , https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000178.v11.p8 , and https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000159.v13.p5.
Evaluation on two independent cohorts. More information can be found on our publication linked under: https://github.com/TRON-Bioinformatics/VariantMedium
Tested on independent data sets: