Summary

This tool allows a user to process neoantigens predicted from vcf files using ANNOVAR and netMHCpan.

Once the primary pipeline is ran, the user is then able to perform Neoantigen recognition potential as described by Marta Luksza et al., Nature 2017. To perform the neoantigen recognition potential please click here

Dependencies

Note: Should be compatible on Darwin and Linux systems, not Windows.

1. Python == 2.7 (Built using Python 2.7.13, not compatible with python 3 yet)
   • biopython == 1.70
2. ANNOVAR
   • Can be downloaded here.
   • ANNOVAR hg19_refGene
   • ANNOVAR hg19_refGeneMrna
   • Other reference builds can be used. Simply change the usr_path.ini file to the appropriate reference (see below).
     • Make sure to use the same one used to call variants.
3. netMHCpan
   • Using netMHCpan-4.0 for all tests of this pipeline.
   • Follow their steps for installation on your platform.
4. PeptideMatch (Only necessary if one wishes to check predicted epitopes for novelty against a reference proteome.)
   • Requires Java.
   • The runnable jar is available here.
   • Download a reference protein sequence in fasta format (e.g. from Ensembl or UniProt) and index it according to the Tutorial.

Installing and preparing environment

1. Clone the repository:

git clone https://github.com/rschenck/NeoPredPipe.git

2. Configure the 'usr_path.ini' file for your environment.
   • All paths within the annovar header should be where you installed annovar.
   • Only one path is needed to the netMHCpan executible under netMHCpan
   • If you wish to use PeptideMatch, provide paths for both jar and reference index.

   Note: You need to provide the absolute path.

3. You can see the options associated by running the following:

python ./main_netMHCpan_pipe.py --help

• Which produces the following:

usage: main_netMHCpan_pipe.py [-h] [-E EPITOPES [EPITOPES ...]] [-l] [-d] [-r]
                              [-p] [-I VCFDIR] [-H HLAFILE] [-o OUTPUTDIR]
                              [-n OUTNAME] [-pp]
                              [-c COLREGIONS [COLREGIONS ...]] [-a] [-t]

optional arguments:
  -h, --help            show this help message and exit
  -E EPITOPES [EPITOPES ...], --epitopes EPITOPES [EPITOPES ...]
                        Epitope lengths for predictions. Default: 8 9 10
  -l                    Specifies whether to delete the ANNOVAR log file.
                        Default: True. Note: Use for debugging.
  -d                    Specified whether to delete intermediate files created
                        by program. Default: True. Note: Set flag to resume
                        job.
  -r, --cleanrun        Specify this alone with no other options to clean-up a
                        run. Be careful that you mean to do this!!
  -p, --preponly        Prep files only without running neoantigen
                        predictions. The prediction step takes the most time.

Required arguments:
  -I VCFDIR             Input vcf file directory location. Example: -I
                        ./Example/input_vcfs/
  -H HLAFILE            HLA file for vcf patient samples.
  -o OUTPUTDIR          Output Directory Path
  -n OUTNAME            Name of the output file for neoantigen predictions

Post Processing Options:
  -pp                   Flag to perform post processing. Default=True.
  -c COLREGIONS [COLREGIONS ...]
                        Columns of regions within vcf that are not normal
                        within a multiregion vcf file after the format field.
                        Example: 0 is normal in test samples, tumor are the
                        other columns. Program can handle different number of
                        regions per vcf file.
  -a                    Flag to not filter neoantigen predictions and keep all
                        regardless of prediction value.
  -m                    Specifies whether to perform check if predicted
                        epitopes match any normal peptide. If set to True,
                        output is added as a column to neoantigens file.
                        Requires PeptideMatch specified in usr_paths.ini.
                        Default=False
  -t                    Flag to turn off a neoantigen burden summary table.
                        Default=True.

Input files

1. VCF file. A standard vcf file with a patient identifier as the title of the .vcf.
2. An hla file with the following tab delimited format:
   • Note, patient identifier in the rows must match that preceding *.vcf
   • Headers are not required but the data should match the format in the table.
   • 'NA' is used when the HLA typing predicts the same HLA subtype for A, B, or C.
   • The program will search for the appropriate allele within netMHCpan alleles list, but care should be taken to ensure accuracy.

Patient	HLA-A_1	HLA-A_2	HLA-B_1	HLA-B_2	HLA-C_1	HLA-C_2
test1	hla_a_31_01_02	hla_a_02_01_80	hla_b_40_01_02	hla_b_50_01_01	hla_c_03_04_20	hla_c_06_02_01_02
test2	hla_a_01_01_01_01	NA	hla_b_07_02_01	NA	hla_c_01_02_01	NA

Run Using Example .vcf files

# Run the Pipeline to only prepare the input files. Can be best to run this independently if working on a cluster.
python main_netMHCpan_pipe.py --preponly -I ./Example/input_vcfs -H ./Example/HLAtypes/hlatypes.txt -o ./ -n TestRun -c 1 2 -E 8 9 10

# Run the Pipeline
python main_netMHCpan_pipe.py -I ./Example/input_vcfs -H ./Example/HLAtypes/hlatypes.txt -o ./ -n TestRun -c 1 2 -E 8 9 10

Data post processing

1. Post processing is turned on by default. If you want it turned off set the '-pp' flag.
2. The output files will yield files with the following information:
   • A file containing the neoantigen predictions with appropriate identifier information and heterogeneity if multiregion.
   • A file containing summaries of the neoantigen burdens in each sample (and regions if multiregion).

Output Format

1. The primary output file of neoantigens has the following format (columns 12-26 are taken from here):
   • Sample: vcf filename/patient identifier
   • R1: Region 1 of a multiregion sample, binary for presence (1) or absence (0). Can be n numbers of regions. Only present in multiregion samples.
   • R2: Region 2 of a multiregion sample, binary for presence (1) or absence (0). Can be n numbers of regions. Only present in multiregion samples.
   • R3: Region 3 of a multiregion sample, binary for presence (1) or absence (0). Can be n numbers of regions. Only present in multiregion samples.
   • Line: Line of within the *.avready file (same as the vcf) to identify mutation yielding corresponding neoantigen.
   • chr: Chromosome of mutation
   • allelepos: Position of the mutation
   • ref: Reference base at the position
   • alt: Alternative base at the location
   • GeneName:RefID: Gene name and RefSeq ID separated by a colon. Multiple genes/refseq IDs separated by a comma.
   • Candidate: Symbol (<=) used to denote a Strong or Week Binder in BindLevel
   • pos: Residue number (starting from 0)
   • hla: Molecule/allele name
   • peptide: Amino acid sequence of the potential ligand
   • core: The minimal 9 amino acid binding core directly in contact with the MHC
   • Of: The starting position of the Core within the Peptide (if > 0, the method predicts a N-terminal protrusion)
   • Gp: Position of the deletion, if any.
   • Gl: Length of the deletion.
   • Ip: Position of the insertions, if any.
   • Il: Length of the insertion.
   • Icore: Interaction core. This is the sequence of the binding core including eventual insertions of deletions.
   • Identity: Protein identifier, i.e. the name of the Fasta entry.
   • Score: The raw prediction score
   • Binding Affinity: Predicted binding affinity in nanoMolar units.
   • Rank: Rank of the predicted affinity compared to a set of random natural peptides. This measure is not affected by inherent bias of certain molecules towards higher or lower mean predicted affinities. Strong binders are defined as having %rank<0.5, and weak binders with %rank<2. We advise to select candidate binders based on %Rank rather than nM Affinity
   • BindLevel: (SB: strong binder, WB: weak binder). The peptide will be identified as a strong binder if the % Rank is below the specified threshold for the strong binders, by default 0.5%. The peptide will be identified as a weak binder if the % Rank is above the threshold of the strong binders but below the specified threshold for the weak binders, by default 2%.
   • Novelty: Binary value for indicating if the epitope is novel (1) or exists in the reference proteome (0). Only present if -m flag is set to perform peptide matching in postprocessing.

Sample	R1	R2	R3	Line	chr	allelepos	ref	alt	GeneName:RefSeqID	pos	hla	peptide	core	Of	Gp	Gl	Ip	Il	Icore	Identity	Score	Rank	Candidate	BindLevel	Novelty
test1	0	1	0	line16	chr1	153914523	G	C	DENND4B:NM_014856	3	HLA-B*40:01	SERQAGAL	SERQAG-AL	0	0	0	6	1	SERQAGAL	line16_NM_01485	0.33670	1.30	<=	WB	1
test1	1	1	0	line8	chr1	53608000	C	T	SLC1A7:NM_001287597,SLC1A7:NM_001287595,SLC1A7:NM_006671,SLC1A7:NM_001287596	2	HLA-C*06:02	LGFFLRTRHL	LFFLRTRHL	0	1	1	0	0	LGFFLRTRHL	line8_NM_001287	0.24655	1.20	<=	WB	1
test2	1	0	0	line34	chr1	248402593	C	A	OR2M4:NM_017504	6	HLA-C*01:02	VMAYERYVAI	VAYERYVAI	0	1	1	0	0	VMAYERYVAI	line34_NM_01750	0.14917	1.50	<=	WB	1
test2	1	1	0	line51	chr2	240982213	C	G	PRR21:NM_001080835	2	HLA-C*01:02	FTHGPSSTPL	FTHPSSTPL	0	3	1	0	0	FTHGPSSTPL	line51_NM_00108	0.22570	0.40	<=	SB	1
test2	1	1	0	line51	chr2	240982213	C	G	PRR21:NM_001080835	7	HLA-C*01:02	SSTPLHPCPF	STPLHPCPF	0	1	1	0	0	SSTPLHPCPF	line51_NM_00108	0.13137	2.00	<=	WB	1

2. If there are not multiple regions from a single patient the resulting summary table will appear as follows (the following are the same for both multiregion below and single region):
   • Sample: Sample identifier
   • Total: Total Neoantigen burdens that are of proper range.
   • Total_WB: Total Neoantigen burdens of weak binding affinity.
   • Total_SB: Total Neoantigen burdens of strong binding affinity.

Sample	Total	Total_WB	Total_SB
Pat1	72	72	0
Pat2	33	23	10

4. If multiple regions are specified then the output will look as follows (scroll left or right to view all):
   • For cases of multiregion samples, the same information for totals are given, but also for each region in the vcf.
   • Heterogeneity (e.g. clonal, subclonal, and shared) information is also measured and printed out. This yields counts of clonal subclonal and shared.
     • For shared neoantigens there must be >2 regions present, otherwise shared will be 0. This pipeline can handle samples with different numbers of regions.

Sample	Total	Total_WB	Total_SB	Total_Region_1	Total_Region_n	Total_WB_Region_1	Total_WB_Region_n	Total_SB_Region_1	Total_SB_Region_n	Clonal	Subclonal	Shared	Clonal_WB	Clonal_SB	Subclonal_WB	Subclonal_SB	Shared_WB	Shared_SB
test1	86	65	21	48	51	0	36	40	0	12	11	0	13	73	0	11	2	54
test2	86	66	20	57	43	0	46	30	0	11	13	0	14	72	0	10	4	56

Important note. The inclusion of indels is still being fully evaluated. Full support for neoantigen prediction for indels will be integrated as an option at a later time. This is not an easy task due to the complex nature of how these variants are predicted to alter peptide sequences.