eXAlu - a deep learning model of Alu retrotransposon exonization
- Download eXAlu here.
- Supporting data for the manuscript:
- Software (archived): eXAlu_main.zip
- List of 870 exonized Alu elements in human frontal cortex: FC_MOAT_v3.txt (from Florea et al., 2021)
- List of 1,091,933 analyzed, and 140,149 predicted, genome-wide Alu elements: hg38_all_Alus_eXAlu.tsv.gz, hg38_predicted_Alus_eXAlu.tsv.gz
- List of 195 polymorphic Alu insertions predicted to be exonized: 1kGP_eXAlu_predictions.tsv
Reference
- He Z, Lui WW, Chen O, Phillips N, Pasquesi GIM, Sabunciyan S, and Florea L (2024). Predicting Alu exonization in the human genome with a deep learning model. Submitted. [Pre-print]
This work was supported in part by NIH grants R01GM129085 and R01GM124531 to L.F..
The Center for Computational Biology at Johns Hopkins University