One error problem occurred caused by data type during using GDCprepare to handle BRCA data

Question

[glaciya2018]

I found one problem when I tried to download the data:

Error in `dplyr::bind_rows()`:
! Can't combine `..368$Tumor_Seq_Allele2` <character> and `..369$Tumor_Seq_Allele2` <logical>.

Is this a problem in the GDC lib function? I can use this function to handle the data from TCGA-BLCA and TCGA-SKCM. But I met this problem when I handle the TCGA-BRCA. Could you please provide any suggestion and solution?

The code can seen below:

query <- GDCquery(
  project = paste0("TCGA-", cancer_type),
  data.category = "Simple Nucleotide Variation", 
  access = "open",
  data.type = "Masked Somatic Mutation", 
  #workflow.type = "MuSE Variant Aggregation and Masking"
  workflow.type = "Aliquot Ensemble Somatic Variant Merging and Masking"
)
GDCdownload(query)
maf <- GDCprepare(query)

The issue came out when this statement runs: maf <- GDCprepare(query). I checked the data structure:

But I don't know which part includes the combining two 368$Tumor_Seq_Allele2 (character) and ..369$Tumor_Seq_Allele2 (logical).

  Hugo_Symbol = col_character(),
  Entrez_Gene_Id = col_double(),
  Center = col_character(),
  NCBI_Build = col_character(),
  Chromosome = col_character(),
  Start_Position = col_double(),
  End_Position = col_double(),
  Strand = col_character(),
  Variant_Classification = col_character(),
  Variant_Type = col_character(),
  Reference_Allele = col_character(),
  Tumor_Seq_Allele1 = col_character(),
  Tumor_Seq_Allele2 = col_character(),
  dbSNP_RS = col_character(),
  dbSNP_Val_Status = col_logical(),
  Tumor_Sample_Barcode = col_character(),
  Matched_Norm_Sample_Barcode = col_character(),
  Match_Norm_Seq_Allele1 = col_logical(),
  Match_Norm_Seq_Allele2 = col_logical(),
  Tumor_Validation_Allele1 = col_logical(),
  Tumor_Validation_Allele2 = col_logical(),
  Match_Norm_Validation_Allele1 = col_logical(),
  Match_Norm_Validation_Allele2 = col_logical(),
  Verification_Status = col_logical(),
  Validation_Status = col_logical(),
  Mutation_Status = col_character(),
  Sequencing_Phase = col_logical(),
  Sequence_Source = col_logical(),
  Validation_Method = col_logical(),
  Score = col_logical(),
  BAM_File = col_logical(),
  Sequencer = col_logical(),
  Tumor_Sample_UUID = col_character(),
  Matched_Norm_Sample_UUID = col_character(),
  HGVSc = col_character(),
  HGVSp = col_character(),
  HGVSp_Short = col_character(),
  Transcript_ID = col_character(),
  Exon_Number = col_character(),
  t_depth = col_double(),
  t_ref_count = col_double(),
  t_alt_count = col_double(),
  n_depth = col_double(),
  n_ref_count = col_logical(),
  n_alt_count = col_logical(),
  all_effects = col_character(),
  Allele = col_character(),
  Gene = col_character(),
  Feature = col_character(),
  Feature_type = col_character(),
  One_Consequence = col_character(),
  Consequence = col_character(),
  cDNA_position = col_character(),
  CDS_position = col_character(),
  Protein_position = col_character(),
  Amino_acids = col_character(),
  Codons = col_character(),
  Existing_variation = col_character(),
  DISTANCE = col_logical(),
  TRANSCRIPT_STRAND = col_double(),
  SYMBOL = col_character(),
  SYMBOL_SOURCE = col_character(),
  HGNC_ID = col_character(),
  BIOTYPE = col_character(),
  CANONICAL = col_character(),
  CCDS = col_character(),
  ENSP = col_character(),
  SWISSPROT = col_character(),
  TREMBL = col_character(),
  UNIPARC = col_character(),
  UNIPROT_ISOFORM = col_character(),
  RefSeq = col_character(),
  MANE = col_character(),
  APPRIS = col_character(),
  FLAGS = col_logical(),
  SIFT = col_character(),
  PolyPhen = col_character(),
  EXON = col_character(),
  INTRON = col_logical(),
  DOMAINS = col_character(),
  `1000G_AF` = col_double(),
  `1000G_AFR_AF` = col_double(),
  `1000G_AMR_AF` = col_double(),
  `1000G_EAS_AF` = col_double(),
  `1000G_EUR_AF` = col_double(),
  `1000G_SAS_AF` = col_double(),
  ESP_AA_AF = col_double(),
  ESP_EA_AF = col_double(),
  gnomAD_AF = col_double(),
  gnomAD_AFR_AF = col_double(),
  gnomAD_AMR_AF = col_double(),
  gnomAD_ASJ_AF = col_double(),
  gnomAD_EAS_AF = col_double(),
  gnomAD_FIN_AF = col_double(),
  gnomAD_NFE_AF = col_double(),
  gnomAD_OTH_AF = col_double(),
  gnomAD_SAS_AF = col_double(),
  MAX_AF = col_double(),
  MAX_AF_POPS = col_character(),
  gnomAD_non_cancer_AF = col_double(),
  gnomAD_non_cancer_AFR_AF = col_double(),
  gnomAD_non_cancer_AMI_AF = col_double(),
  gnomAD_non_cancer_AMR_AF = col_double(),
  gnomAD_non_cancer_ASJ_AF = col_double(),
  gnomAD_non_cancer_EAS_AF = col_double(),
  gnomAD_non_cancer_FIN_AF = col_double(),
  gnomAD_non_cancer_MID_AF = col_double(),
  gnomAD_non_cancer_NFE_AF = col_double(),
  gnomAD_non_cancer_OTH_AF = col_double(),
  gnomAD_non_cancer_SAS_AF = col_double(),
  gnomAD_non_cancer_MAX_AF_adj = col_double(),
  gnomAD_non_cancer_MAX_AF_POPS_adj = col_character(),
  CLIN_SIG = col_character(),
  SOMATIC = col_character(),
  PUBMED = col_logical(),
  TRANSCRIPTION_FACTORS = col_logical(),
  MOTIF_NAME = col_logical(),
  MOTIF_POS = col_logical(),
  HIGH_INF_POS = col_logical(),
  MOTIF_SCORE_CHANGE = col_logical(),
  miRNA = col_logical(),
  IMPACT = col_character(),
  PICK = col_double(),
  VARIANT_CLASS = col_character(),
  TSL = col_double(),
  HGVS_OFFSET = col_double(),
  PHENO = col_character(),
  GENE_PHENO = col_double(),
  CONTEXT = col_character(),
  tumor_bam_uuid = col_character(),
  normal_bam_uuid = col_character(),
  case_id = col_character(),
  GDC_FILTER = col_logical(),
  COSMIC = col_character(),
  hotspot = col_character(),
  RNA_Support = col_character(),
  RNA_depth = col_logical(),
  RNA_ref_count = col_logical(),
  RNA_alt_count = col_logical(),
  callers = col_character()