.. image:: ../images/pVACfuse_logo_trans-bg_sm_v4b.png
:align: right
:alt: pVACfuse logo
Features
========
**Fusion analysis**
pVACfuses proceses fusion variants annotated by AGFusion or Arriba.
**No local install of epitope prediction software needed**
pVACfuse 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**
pVACfuse 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 :ref:`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. pVACfuse supports binding affinity algorithms as well as elution
algortihms.
By using the IEDB RESTful web interface, pVACfuse 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
pVACfuse run. pVACfuse also support the option of filtering on allele-specific binding thresholds
as recommended by `IEDB `_.
as well as percentile ranks.
Additional filtering on the binding affitinity can be manually done by the user by running the
:ref:`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.
Read support and expression data are extracted from a star-fusion.fusion_predictions.tsv or star-fusion.fusion_predictions.abridged.tsv,
when provided, in order to automatically filter with
adjustable thresholds. The user can also manually run
the :ref:`standalone coverage filter ` to further narrow down their results
from the filtered output file.
pVACfuse also runs a top score filter to only keep the top scoring epitope
for each fusion. This filter can also be run
:ref:`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.