Features

FASTA support

pVACbind uses a FASTA file as its input. All FASTA entries will be processed by pVACbind unless they are shorter than the chosen epitope length or contain unsupported characters.

No local install of epitope prediction software needed

pVACbind utilizes the IEDB RESTful web interface. This means that none of the underlying prediction software, like NetMHC, needs to be installed locally.

Warning

We only recommend using the RESTful API for small requests. If you use the RESTful API to process large VCFs or to make predictions for many alleles, epitope lengths, or prediction algorithms, you might overload their system. This can result in the blacklisting of your IP address by IEDB, causing 403 errors when trying to use the RESTful API. In that case please open a ticket with IEDB support to have your IP address removed from the IEDB blacklist.

Support for local installation of the IEDB Analysis Resources

pVACbind provides the option of using a local installation of the IEDB MHC class I and class II binding prediction tools.

Warning

Using a local IEDB installation is strongly recommended for larger datasets or when the making predictions for many alleles, epitope lengths, or prediction algorithms. More information on how to install IEDB locally can be found on the Installation page (note: the pvactools docker image now contains IEDB).

MHC Class I and Class II predictions

Both MHC Class I and Class II predictions are supported. Simply choose the desired prediction algorithms and HLA alleles during processing and Class I and Class II prediction results will be written to their own respective subdirectories in your output directory.

By using the IEDB RESTful web interface, pVACbind leverages their extensive support of different prediction algorithms.

In addition to IEDB-supported prediction algorithms, we’ve also added support for MHCflurry and MHCnuggets.

MHC Class I Binding Affinity Prediction Algorithm	Version	Supports Percentile Rank
NetMHCpan	4.1	yes
NetMHC	4.0	yes
NetMHCcons	1.1	yes
PickPocket	1.1	yes
SMM	1.0	yes
SMMPMBEC	1.0	yes
MHCflurry		yes
MHCnuggets		no

MHC Class II Binding Affinity Prediction Algorithm	Version	Supports Percentile Rank
NetMHCIIpan	4.1	yes
SMMalign	1.1	yes
NNalign	2.3	yes
MHCnuggets		no

MHC Class I Elution Prediction Algorithm	Version	Supports Percentile Rank
NetMHCpanEL	4.1	yes
MHCflurryEL		Processing Score: no; Presentation Score: yes
BigMHC_EL		no

MHC Class II Elution Prediction Algorithm	Version	Supports Percentile Rank
NetMHCIIpanEL	4.1	yes

MHC Class I Immunogenicity Prediction Algorithm	Version	Supports Percentile Rank
BigMHC_IM		no
DeepImmuno		no

Comprehensive filtering

Automatic filtering on the binding affinity ic50 (nm) value narrows down the results to only include “good” candidate peptides. The binding filter threshold can be adjusted by the user for each pVACbind run. pVACbind also support the option of filtering on allele-specific binding thresholds as recommended by IEDB. Additional filtering on the binding affitinity can be manually done by the user by running the standalone binding filter on the filtered result file to narrow down the candidate epitopes even further or on the unfiltered all_epitopes file to apply different cutoffs.

pVACbind also runs a top score filter to only keep the top scoring epitope for each FASTA sequence. This filter can also be run standalone.

NetChop and NetMHCstab integration

Cleavage position predictions are added with optional processing through NetChop.

Stability predictions can be added if desired by the user. These predictions are obtained via NetMHCstabpan.

Reference proteome similarity analysis

This optional feature will search for an epitope in the reference proteome using BLAST or a reference proteome FASTA file to determine if the epitope occurs elsewhere in the proteome and is, therefore, not tumor-specific.

Problematic amino acids

This optional feature allows users to specify a list of amino acids that would be considered problematic to occur either everywhere or at specific positions in a neoepitope. This can be useful when certain amino acids would be problematic during peptide manufacturing.