miniGENIE is an easy-to-use, Python-based software package designed to automate the generation of synthesis-ready minigene libraries for high-throughput T-cell dropout screens. The workflow accepts predicted antigens from both the nextNEOpi (canonical neoantigens) and NovumRNA (non-canonical TSAs) pipelines, and it can additionally process custom user-provided protein sequences in FASTA format. For each input antigen, miniGENIE constructs minigenes of user-defined length, optionally pairing mutant and corresponding wild-type reference sequences when available. All candidate constructs are then checked against the reference proteome and matches are flagged. The sequences are subsequently back-translated and codon-optimized for efficient expression, followed by the removal of user-defined undesirable sequence features such as restriction enzyme recognition sites and repetitive motifs. In the final step, adapters and barcodes are appended and ready-to-order minigene libraries are provided as fasta output as well as a fully annotated table in the xlsx format.
miniGENIEpy is a python package which works as a standalone software to generate minigenes from fasta files or the respective output files from nextNEOpi or NovumRNA. miniGENIEnf is coming soon and implements minigenie as a nextflow module to integrate it into existing or new nextflow pipelines.
For installation instructions look up the README in the respective python or nextflow folder