In hase62/Neoantimon: Neoantimon: A multifunctional R package for identification of tumor-specific neoantigens

Data Preparation and Sample Codes for Analysis

#install.packages('devtools');
library(devtools);
install_github('hase62/Neoantimon');
library(Neoantimon);
if (!requireNamespace("BiocManager", quietly = TRUE))
    install.packages("BiocManager")
BiocManager::install("biomaRt")
library(biomaRt)

To calculate the binding affinity of neoantigen candaites, which are generated from from SNVs, to HLA ClassI. When using MHCflurry, [[1]] and [[2]] include the results of NetMHCpan and MHCflurry, respectively.

Result_HLA1_SNV <- MainSNVClass1(input_annovar_format_file = "data/sample_vcf.annovar.txt",
                                   file_name_in_hla_table = "sample",
                                   hla_file = "data/sample_hla_table_c1.txt",
                                   refflat_file  = "refFlat.grch37.txt",
                                   refmrna_file = "refMrna.grch37.fa",
                                   rnaexp_file = "data/sample_rna_exp.txt",
                                   netMHCpan_dir = "netMHCpan-4.0/netMHCpan",
                                   depth_tumor_column = 12,
                                   depth_normal_column = 14,
                                   SNPs = "data/sample_vcf.snps.vcf",
                                   multiple_variants = TRUE,
                                   MHCflurry = "~/opt/anaconda3/bin/mhctools")
  Result_HLA1_SNV_1 <- CalculatePriorityScores(result = Result_HLA1_SNV[[1]], useRNAvaf = FALSE)
  Result_HLA1_SNV_2 <- CalculatePriorityScores(result = Result_HLA1_SNV[[2]], useRNAvaf = FALSE)
  print(head(Result_HLA1_SNV_1))

  print(Export_Summary_SNV(Input = Result_HLA1_SNV_1, Mut_IC50_th = 500, Wt_IC50_th = 500))

 Result_HLA1_SNV_vep <- MainSNVClass1(input_vep_format_file = "data/sample_vcf.vep.txt",
                                   file_name_in_hla_table = "sample",
                                   hla_file = "data/sample_hla_table_c1.txt",
                                   refflat_file  = "refFlat.grch37.txt",
                                   refmrna_file = "refMrna.grch37.fa",
                                   rnaexp_file = "data/sample_rna_exp.txt",
                                   netMHCpan_dir = "netMHCpan-4.0/netMHCpan",
                                   multiple_variants = FALSE)
  Result_HLA1_vep_SNV <- CalculatePriorityScores(result = Result_HLA1_SNV_vep, useRNAvaf = FALSE)  
  print(head(Result_HLA1_vep_SNV))

  print(Export_Summary_SNV(Input = Result_HLA1_vep_SNV, Mut_IC50_th = 500, Wt_IC50_th = 500))

To calculate the binding affinity of neoantigen candaites, which are generated from from SNVs, to HLA ClassII.

 Result_HLA2_SNV <- MainSNVClass2(input_annovar_format_file = "data/sample_vcf.annovar.txt",
                                   file_name_in_hla_table = "sample",
                                   hla_file = "data/sample_hla_table_c2.txt",
                                   refflat_file  = "refFlat.grch37.txt",
                                   refmrna_file = "refMrna.grch37.fa",
                                   rnaexp_file = "data/sample_rna_exp.txt",
                                   netMHCIIpan_dir = "netMHCIIpan-3.2/netMHCIIpan",
                                   depth_tumor_column = 12,
                                   depth_normal_column = 14,
                                   SNPs = "data/sample_vcf.snps.vcf",
                                   multiple_variants = TRUE)
  Result_HLA2_SNV <- CalculatePriorityScores(result = Result_HLA2_SNV, useRNAvaf = FALSE) 
  print(head(Result_HLA2_SNV))

  print(Export_Summary_SNV(Input = Result_HLA2_SNV, Mut_IC50_th = 500, Wt_IC50_th = 500))

To calculate the binding affinity of neoantigen candaites, which are generated from from indels, to HLA ClassI. When using MHCflurry, [[1]] and [[2]] include the results of NetMHCpan and MHCflurry, respectively.

Result_HLA1_INDEL <- MainINDELClass1(input_annovar_format_file = "data/sample_vcf.annovar.txt",
                                       file_name_in_hla_table = "sample",
                                       hla_file = "data/sample_hla_table_c1.txt",
                                       refflat_file  = "refFlat.grch37.txt",
                                       refmrna_file = "refMrna.grch37.fa",
                                       rnaexp_file = "data/sample_rna_exp.txt",
                                       netMHCpan_dir = "netMHCpan-4.0/netMHCpan",
                                       depth_tumor_column = 12,
                                       depth_normal_column = 14,
                                       SNPs = "data/sample_vcf.snps.vcf",
                                       multiple_variants = TRUE,
                                       MHCflurry = "~/opt/anaconda3/bin/mhctools")
  Result_HLA1_INDEL_1 <- CalculatePriorityScores(result = Result_HLA1_INDEL[[1]], useRNAvaf = FALSE)
  Result_HLA1_INDEL_2 <- CalculatePriorityScores(result = Result_HLA1_INDEL[[2]], useRNAvaf = FALSE)
  print(head(Result_HLA1_INDEL_1))

  print(Export_Summary_IndelSV(Input = Result_HLA1_INDEL_1, Mut_IC50_th = 500))

  print(Export_Summary_IndelSV_perFragments(Input = Result_HLA1_INDEL_1, Mut_IC50_th = 500))

To calculate the binding affinity of neoantigen candaites, which are generated from from indels, to HLA ClassII.

  Result_HLA2_INDEL <- MainINDELClass2(input_annovar_format_file = "data/sample_vcf.annovar.txt",
                                       file_name_in_hla_table = "sample",
                                       hla_file = "data/sample_hla_table_c2.txt",
                                       refflat_file  = "refFlat.grch37.txt",
                                       refmrna_file = "refMrna.grch37.fa",
                                       rnaexp_file = "data/sample_rna_exp.txt",
                                       netMHCIIpan_dir = "netMHCIIpan-3.2/netMHCIIpan",
                                       depth_tumor_column = 12,
                                       depth_normal_column = 14,
                                       SNPs = "data/sample_vcf.snps.vcf",
                                       multiple_variants = TRUE)

  Result_HLA2_INDEL <- CalculatePriorityScores(result = Result_HLA2_INDEL, useRNAvaf = FALSE)  
  print(head(Result_HLA2_INDEL))

  print(Export_Summary_IndelSV(Input = Result_HLA2_INDEL, Mut_IC50_th = 500))

  print(Export_Summary_IndelSV_perFragments(Input = Result_HLA2_INDEL, Mut_IC50_th = 500))

To calculate the binding affinity of neoantigen candaites, which are generated from from SVs, to HLA ClassI.

  Result_HLA1_SV <- MainSVFUSIONClass1(input_file = "data/sample_sv_bnd.txt",
                                       file_name_in_hla_table = "sample",
                                       hla_file = "data/sample_hla_table_c1.txt",
                                       refflat_file  = "refFlat.grch37.txt",
                                       refmrna_file = "refMrna.grch37.fa",
                                       rnaexp_file = "data/sample_rna_exp.txt",
                                       netMHCpan_dir = "netMHCpan-4.0/netMHCpan",
                                       refdna_file = "GRCh37.fa",
                                       mutation_alt_bnd_column = 5,
                                       gene_symbol_column = 7,
                                       mate_id_column = 8)
  Result_HLA1_SV <- CalculatePriorityScores(result = Result_HLA1_SV, useRNAvaf = FALSE)
  print(head(Result_HLA1_SV))

  print(Export_Summary_IndelSV(Result_HLA1_SV, Mut_IC50_th = 500))

  print(Export_Summary_IndelSV_perFragments(Result_HLA1_SV, Mut_IC50_th = 500))

To calculate the binding affinity of neoantigen candaites, which are generated from from SVs, to HLA ClassII.

  Result_HLA2_SV <- MainSVFUSIONClass2(input_file = "data/sample_sv_bnd.txt",
                                       file_name_in_hla_table = "sample",
                                       hla_file = "data/sample_hla_table_c2.txt",
                                       refflat_file  = "refFlat.grch37.txt",
                                       refmrna_file = "refMrna.grch37.fa",
                                       rnaexp_file = "data/sample_rna_exp.txt",
                                       netMHCIIpan_dir = "netMHCIIpan-3.2/netMHCIIpan",
                                       refdna_file = "GRCh37.fa",
                                       mutation_alt_bnd_column = 5,
                                       gene_symbol_column = 7,
                                       mate_id_column = 8)
  Result_HLA2_SV <- CalculatePriorityScores(result = Result_HLA2_SV, useRNAvaf = FALSE)
  print(head(Result_HLA2_SV))

  print(Export_Summary_IndelSV(Result_HLA2_SV, Mut_IC50_th = 500))

  print(Export_Summary_IndelSV_perFragments(Result_HLA2_SV, Mut_IC50_th = 500))

To calculate the binding affinity of neoantigen candaites, which are directly generated from RNA sequences, to HLA ClassI. The peptides included in the original genes ("NM_003998", "NM_001165412") are removed from the results.

   Result_HLA1_Seq <- MainSeqFragmentClass1(input_sequence = "atggcagaagatgatccatatttgggaaggcctgaaaaaatgtttcatttggatccttctttgactcatacaatatttaatc",
                                           file_name_in_hla_table = "sample",
                                           hla_file = "data/sample_hla_table_c1.txt",
                                           hmdir = getwd(),
                                           job_id = "NO_job_id",
                                           refflat_file  = "refFlat.grch37.txt",
                                           refmrna_file = "refMrna.grch37.fa",
                                           netMHCpan_dir = "netMHCpan-4.0/netMHCpan",
                                           reference_nm_id = c("NM_003998", "NM_001165412"))
  Result_HLA1_Seq <- CalculatePriorityScores(result = Result_HLA1_Seq, useRNAvaf = FALSE)
  print(head(Result_HLA1_Seq))

  print(Export_Summary_Fragments(Result_HLA1_Seq, Mut_IC50_th = 500))

To calculate the binding affinity of neoantigen candaites, which are directly generated from RNA sequences, to HLA ClassII. The peptides included in the riginal genes ("NFKB1", "BCL3") are removed from the results.

  Result_HLA2_Seq <- MainSeqFragmentClass2(input_sequence = "atggcagaagatgatccatatttgggaaggcctgaacaaatgtttcatttgatccttctttgactcatacaatatttaatc",
                                           file_name_in_hla_table = "sample",
                                           hla_file = "data/sample_hla_table_c2.txt",
                                           hmdir = getwd(),
                                           job_id = "NO_job_id",
                                           refflat_file  = "refFlat.grch37.txt",
                                           refmrna_file = "refMrna.grch37.fa",
                                           netMHCIIpan_dir = "netMHCIIpan-3.2/netMHCIIpan",
                                           reference_gene_symbol = c("NFKB1", "BCL3"))
  Result_HLA2_Seq <- CalculatePriorityScores(result = Result_HLA2_Seq, useRNAvaf = FALSE)
  print(head(Result_HLA2_Seq))

  print(Export_Summary_Fragments(Result_HLA2_Seq, Mut_IC50_th = 500))

hase62/Neoantimon documentation built on Sept. 21, 2023, 4:23 p.m.