val_ag_name() validation of name of binding locus
val_ag_name(ag_present)preproc(allele_in, link)
pull_seq(alleles_in, tbl_ref_in)
comb_pred_tbl(nm_method, nm_sht, nm_fd, thold_score, thold_rank)
comb_pred_tbl_mhcI(nm_method, nm_fd, thold_score, thold_rank)
find_nonself(dat_in)
pull_ag_self(vec_in)
find_core_mut(dat_in)
align_seq(seq1, seq2, gapopening = 0, gapextension = 8)
pull_obj_name(x)
a vector of locus name(s) to make binding predictions for
preproc() format and validate allele names
a vector contains allele name(s)
a string of url of MHC I or II api
pull_seq() pull out sequence of each allele based on ref table
vector, allele names
dataframe, reference table, default is human_all.csv from github
comb_pred_tbl() combine individual prediction tables by method, exclude none-binders and keep strong and weak binders only
string, prediction method used for IEDB prediction
string, short name of alleles
string, folder name which contains predict tables from IEDB
list of vectors, binder thresholds by ic50 score
vector, binder thresholds by percentile rank
find_nonself() find nonself binding peptides
dataframe with pep_stim, core, pep_self selected from pull_ag_self
align_seq() align protein sequences
dataframe with pep_stim, core, aligned ag_stim and ag_self columns
find_core_mut() find mutation position to core
string, unaligned sequence of ag_stim
string, unaligned sequence of ag_self
numeric, the cost for opening a gap in the alignment.
numeric, the incremental cost incurred along the length of the gap in the alignment
pull_obj_name()
name of an object