REAGENT or RESOURCE	SOURCE	IDENTIFIER
Deposited data
EDGE MS ligand dataset	MassIVE Archive (http://massive.ucsd.edu)	MSV000082648
EDGE RNA-Seq	Bullik-Sullivan et al. (Bulik-Sullivan et al., 2018)	Data S9 (in original source)
Sarkizova MS ligand dataset	MassIVE Archive (http://massive.ucsd.edu)	MSV000084172 and MSV000080527
Sarkizova RNA-Seq	GEO	GSE93315
Sarkizova MS ligand cancer patient datasets (independent benchmark)	MassIVE Archive (http://massive.ucsd.edu)	MSV000084442
Trolle MS ligand dataset	IEDB (Vita et al., 2019)	http://www.iedb.org/subID/1000685
Trolle RNA-Seq (HeLa cell line)	GEO	GSM3899456
NCI neoantigen dataset	Gartner et al. (Gartner et al., 2021)	Table S2 (in original source)
IEDB epitopes (independent benchmark)	Reynisson et al. (Reynisson et al., 2021)	Mendeley data: https://doi.org/10.17632/mf3c8n3w53.1
Yellow Fever Virus epitopes (independent benchmark)	Stryhn et al. (Stryhn et al., 2020)	Mendeley data: https://doi.org/10.17632/4zg276pgh2.1
TESLA neoepitopes (independent benchmark)	Wells et al. (Wells et al., 2020)	Mendeley data: https://doi.org/10.17632/6x87nx8jtc.1
Human Protein Atlas reference RNA-Seq dataset	Human Protein Atlas (Uhlén et al., 2015)	Mendeley data: https://doi.org/10.17632/bn3htx2459.1
PAXdb reference Proteomics dataset	PAXdb (Wang et al., 2015)	Mendeley data: https://doi.org/10.17632/fc434cn5rk.1
Software and algorithms
NetMHCpan-4.1	Reynisson et al. (Reynisson et al., 2021)	https://services.healthtech.dtu.dk/service.php?NetMHCpan-4.1
Python	Python	https://www.python.org
Other
Main executable file used to train NetMHCpanExp	https://services.healthtech.dtu.dk/services/NetMHCpanExp-1.0/code/nnalign_exp_train	–
Training datasets (and other additional files required for training)	https://services.healthtech.dtu.dk/suppl/immunology/NetMHCpanExp-1.0/training_files/	–
Main executable file used to evaluate NetMHCpanExp	https://services.healthtech.dtu.dk/services/NetMHCpanExp-1.0/code/nnalign_exp_eval	–
Evaluation datasets	https://services.healthtech.dtu.dk/service.php?NetMHCpanExp-1.0, by clicking on the “Evaluation data sets” tab.	–