UsageΒΆ
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.
usage: pvacfuse run [-h] [--iedb-install-directory IEDB_INSTALL_DIRECTORY]
[-r IEDB_RETRIES] [-k] [-t N_THREADS]
[--netmhciipan-version {4.3,4.2,4.1,4.0}]
[-e1 CLASS_I_EPITOPE_LENGTH] [-e2 CLASS_II_EPITOPE_LENGTH]
[-b BINDING_THRESHOLD]
[--percentile-threshold PERCENTILE_THRESHOLD]
[--percentile-threshold-strategy {conservative,exploratory}]
[--allele-specific-binding-thresholds]
[-m {lowest,median}] [-m2 {ic50,percentile}]
[--net-chop-method {cterm,20s}] [--netmhc-stab]
[--net-chop-threshold NET_CHOP_THRESHOLD]
[--problematic-amino-acids PROBLEMATIC_AMINO_ACIDS]
[--run-reference-proteome-similarity]
[--blastp-path BLASTP_PATH]
[--blastp-db {refseq_select_prot,refseq_protein}]
[--peptide-fasta PEPTIDE_FASTA] [-a {sample_name}]
[-s FASTA_SIZE] [--exclude-NAs]
[-d DOWNSTREAM_SEQUENCE_LENGTH]
[--genes-of-interest-file GENES_OF_INTEREST_FILE]
[--aggregate-inclusion-binding-threshold AGGREGATE_INCLUSION_BINDING_THRESHOLD]
[--aggregate-inclusion-count-limit AGGREGATE_INCLUSION_COUNT_LIMIT]
[--starfusion-file STARFUSION_FILE]
[--read-support READ_SUPPORT] [--expn-val EXPN_VAL]
input_file sample_name allele
{BigMHC_EL,BigMHC_IM,DeepImmuno,MHCflurry,MHCflurryEL,MHCnuggetsI,MHCnuggetsII,NNalign,NetMHC,NetMHCIIpan,NetMHCIIpanEL,NetMHCcons,NetMHCpan,NetMHCpanEL,PickPocket,SMM,SMMPMBEC,SMMalign,all,all_class_i,all_class_ii}
[{BigMHC_EL,BigMHC_IM,DeepImmuno,MHCflurry,MHCflurryEL,MHCnuggetsI,MHCnuggetsII,NNalign,NetMHC,NetMHCIIpan,NetMHCIIpanEL,NetMHCcons,NetMHCpan,NetMHCpanEL,PickPocket,SMM,SMMPMBEC,SMMalign,all,all_class_i,all_class_ii} ...]
output_dir
Run the pVACfuse pipeline
positional arguments:
input_file An AGFusion output directory or Arriba fusion.tsv
output file.
sample_name The name of the sample being processed. This will be
used as a prefix for output files.
allele Name of the allele to use for epitope prediction.
Multiple alleles can be specified using a comma-
separated list. For a list of available alleles, use:
`pvacfuse valid_alleles`.
{BigMHC_EL,BigMHC_IM,DeepImmuno,MHCflurry,MHCflurryEL,MHCnuggetsI,MHCnuggetsII,NNalign,NetMHC,NetMHCIIpan,NetMHCIIpanEL,NetMHCcons,NetMHCpan,NetMHCpanEL,PickPocket,SMM,SMMPMBEC,SMMalign,all,all_class_i,all_class_ii}
The epitope prediction algorithms to use. Multiple
prediction algorithms can be specified, separated by
spaces.
output_dir The directory for writing all result files.
optional arguments:
-h, --help show this help message and exit
--iedb-install-directory IEDB_INSTALL_DIRECTORY
Directory that contains the local installation of IEDB
MHC I and/or MHC II. (default: None)
-r IEDB_RETRIES, --iedb-retries IEDB_RETRIES
Number of retries when making requests to the IEDB
RESTful web interface. Must be less than or equal to
100. (default: 5)
-k, --keep-tmp-files Keep intermediate output files. This might be useful
for debugging purposes. (default: False)
-t N_THREADS, --n-threads N_THREADS
Number of threads to use for parallelizing peptide-MHC
binding prediction calls. (default: 1)
--netmhciipan-version {4.3,4.2,4.1,4.0}
Specify the version of NetMHCIIpan or NetMHCIIpanEL to
be used during the run. (default: 4.1)
-e1 CLASS_I_EPITOPE_LENGTH, --class-i-epitope-length CLASS_I_EPITOPE_LENGTH
Length of MHC Class I subpeptides (neoepitopes) to
predict. Multiple epitope lengths can be specified
using a comma-separated list. Typical epitope lengths
vary between 8-15. Required for Class I prediction
algorithms. (default: [8, 9, 10, 11])
-e2 CLASS_II_EPITOPE_LENGTH, --class-ii-epitope-length CLASS_II_EPITOPE_LENGTH
Length of MHC Class II subpeptides (neoepitopes) to
predict. Multiple epitope lengths can be specified
using a comma-separated list. Typical epitope lengths
vary between 11-30. Required for Class II prediction
algorithms. (default: [12, 13, 14, 15, 16, 17, 18])
-b BINDING_THRESHOLD, --binding-threshold BINDING_THRESHOLD
When creating the filtered.tsv report, only include
epitopes where the mutant allele has ic50 binding
scores below this value. When creating the
aggreated.tsv report, only bin candidates into the
Pass tier that meet this threshold. (default: 500)
--percentile-threshold PERCENTILE_THRESHOLD
When creating the filtered.tsv report, only include
epitopes where the mutant allele has a percentile rank
below this value. When creating the aggregated.tsv
report, only bin candidates into the Pass tier that
meet this threshold. (default: None)
--percentile-threshold-strategy {conservative,exploratory}
Specify the candidate inclusion strategy. The
'conservative' option requires a candidate to pass
BOTH the binding threshold and percentile threshold
(default). The 'exploratory' option requires a
candidate to pass EITHER the binding threshold or the
percentile threshold. (default: conservative)
--allele-specific-binding-thresholds
Use allele-specific binding thresholds. To print the
allele-specific binding thresholds run `pvacfuse
allele_specific_cutoffs`. If an allele does not have a
special threshold value, the `--binding-threshold`
value will be used. (default: False)
-m {lowest,median}, --top-score-metric {lowest,median}
The ic50 scoring metric to use when filtering epitopes
by binding-threshold or minimum fold change. lowest:
Use the best MT Score and Corresponding Fold Change
(i.e. the lowest MT ic50 binding score and
corresponding fold change of all chosen prediction
methods). median: Use the median MT Score and Median
Fold Change (i.e. the median MT ic50 binding score and
fold change of all chosen prediction methods).
(default: median)
-m2 {ic50,percentile}, --top-score-metric2 {ic50,percentile}
Whether to use median/best IC50 or to use median/best
percentile score when determining the best peptide in
the aggregated report and the top score filter
(filtered report). This parameter is also used to
influence the primary sorting criteria in the
aggregated report for the candidates within each tier
as well as in the filtered report. (default: ic50)
--net-chop-method {cterm,20s}
NetChop prediction method to use ("cterm" for C term
3.0, "20s" for 20S 3.0). C-term 3.0 is trained with
publicly available MHC class I ligands and the authors
believe that is performs best in predicting the
boundaries of CTL epitopes. 20S is trained with in
vitro degradation data. (default: None)
--netmhc-stab Run NetMHCStabPan after all filtering and add
stability predictions to predicted epitopes. (default:
False)
--net-chop-threshold NET_CHOP_THRESHOLD
NetChop prediction threshold (increasing the threshold
results in better specificity, but worse sensitivity).
(default: 0.5)
--problematic-amino-acids PROBLEMATIC_AMINO_ACIDS
A list of amino acids to consider as problematic.
During aggregate report creation, only candidates
without problematic positions will be binned into the
Pass tier. Each entry can be specified in the
following format: `amino_acid(s)`: One or more one-
letter amino acid codes. Any occurrence of this amino
acid string, regardless of the position in the
epitope, is problematic. When specifying more than one
amino acid, they will need to occur together in the
specified order. `amino_acid:position`: A one letter
amino acid code, followed by a colon separator,
followed by a positive integer position (one-based).
The occurrence of this amino acid at the position
specified is problematic., E.g. G:2 would check for a
Glycine at the second position of the epitope. The
N-terminus is defined as position 1.
`amino_acid:-position`: A one letter amino acid code,
followed by a colon separator, followed by a negative
integer position. The occurrence of this amino acid at
the specified position from the end of the epitope is
problematic. E.g., G:-3 would check for a Glycine at
the third position from the end of the epitope. The
C-terminus is defined as position -1. (default: None)
--run-reference-proteome-similarity
Blast peptides against the reference proteome or
search for peptides in a reference proteome fasta
file. During aggregate report creation, only
candidates without a reference proteome match will be
binned into the Pass tier. (default: False)
--blastp-path BLASTP_PATH
Blastp installation path. (default: None)
--blastp-db {refseq_select_prot,refseq_protein}
The blastp database to use. (default:
refseq_select_prot)
--peptide-fasta PEPTIDE_FASTA
When running the reference proteome similarity step,
use this reference peptide FASTA file to find matches
instead of blastp. (default: None)
-a {sample_name}, --additional-report-columns {sample_name}
Additional columns to output in the final report. If
sample_name is chosen, this will add a column with the
sample name in every row of the output. This can be
useful if you later want to concatenate results from
multiple individuals into a single file. (default:
None)
-s FASTA_SIZE, --fasta-size FASTA_SIZE
Number of FASTA entries per IEDB request. For some
resource-intensive prediction algorithms like
Pickpocket and NetMHCpan it might be helpful to reduce
this number. Needs to be an even number. (default:
200)
--exclude-NAs Exclude NA values from the filtered output. (default:
False)
-d DOWNSTREAM_SEQUENCE_LENGTH, --downstream-sequence-length DOWNSTREAM_SEQUENCE_LENGTH
Cap to limit the downstream sequence length for
frameshifts when creating the FASTA file. Use 'full'
to include the full downstream sequence. (default:
1000)
--genes-of-interest-file GENES_OF_INTEREST_FILE
A genes of interest file. Predictions resulting from
variants on genes in this list will be marked in the
result files. The file should be formatted to have
each gene on a separate line without a header line. If
no file is specified, the Cancer Gene Census list of
high-confidence genes is used as the default.
(default: None)
--aggregate-inclusion-binding-threshold AGGREGATE_INCLUSION_BINDING_THRESHOLD
Threshold for including epitopes when creating the
aggregate report (default: 5000)
--aggregate-inclusion-count-limit AGGREGATE_INCLUSION_COUNT_LIMIT
Limit neoantigen candidates included in the aggregate
report to only the best n candidates per variant.
(default: 15)
--starfusion-file STARFUSION_FILE
Path to a star-fusion.fusion_predictions.tsv or star-
fusion.fusion_predictions.abridged.tsv to extract read
support and expression information from. When running
with AGFusion data, both read support and expression
data from this file will be used. When running with
Arriba data, only expression data from this file is
used while read support data will be parsed from the
Arriba data directly. (default: None)
--read-support READ_SUPPORT
Read Support Cutoff. When creating the filtered.tsv
report, only include epitopes with a read support
above this value. When creating the aggregated.tsv
report, only bin candidates into the Pass tier that
meet this threshold. (default: 5)
--expn-val EXPN_VAL Expression Cutoff. Expression is meassured as FFPM
(fusion fragments per million total reads). When
creating the filtered.tsv report, only include
epitopes with expression above this value. When
creating the aggregated.tsv report, only bin
candidates into the Pass tier that meet this
threshold. (default: 0.1)