View source: R/VDJ_antigen_integrate.R
VDJ_antigen_integrate | R Documentation |
Integrate antigen-specific information from a list of antigen dataframes or antigen csv file paths. The antigen data should contain either the clonotypes, cell barcodes, or sequences with the specific column names of the VDJ/VDJ.GEX.matrix[[1]] object. These columns will be used to rematch the binder information at the cell, sequence, or clonotype level into the main VDJ.GEX.matrix[[1]].
VDJ_antigen_integrate(
VDJ,
antigen.data.list,
antigen.features,
binder.threshold,
VDJ.VJ.1chain,
match.by,
matching.type,
distance.threshold,
cores,
sample.id,
aberrant.chosen.sequences,
output.format
)
VDJ |
VDJ or VDJ.GEX.matrix[[1]] object, as obtained from the VDJ_GEX_matrix function in Platypus. |
antigen.data.list |
list of antigen csv file paths or antigen dataframes for the specific antigen datasets. To ease matching, the column names by which we will match should be the same as the column names in the original VDJ/VDJ.GEX.matrix[[1]] object. |
antigen.features |
vector of columns of antigen features to be integrated from the antigen csv files into the VDJ/VDJ.GEX.matrix[[1]] object. The vector can also use unique, short-hand names of the columns to add (e.g., 'affinity' for 'octet.affinity.[nM]'). |
binder.threshold |
list or nested list of threshold values and specific features by which to define binders in the VDJ. For example, if binder.threshold=list(list('affinity', 0.2), list('elisa', 0.8)), we will have two new binder columns: binders_affinity if the values are greater than 0.2, binders_elisa if they are greater than 0.8. |
VDJ.VJ.1chain |
boolean, if T will remove aberrant cells (more than 1 VDJ of VJ chain), if F it will keep them in the VDJ when matching antigen data. |
match.by |
string, represents the method by which to match the antigen data and integrate it into the VDJ/VDJ.GEX.matrix[[1]] object. 'clonotype' will match by 'clonotype_id' (needs to be present in the antigen data), 'clonotype.v3' will match by v3 cellranger clonotypes (you need a v3_clonotypes column in the VDJ/VDJ.GEX.matrix[[1]], 'cdr3.aa' by VDJ and VJ cdr3s amino acid sequences, 'cdrh3.aa' by VDJ cdr3s amino acid sequences, 'VDJ.VJ.aa' by full VDJ and VJ aa sequences, 'VDJ.VJ.nt' by trimmed nt VDJ and VJ sequences (must run VDJ_call_MIXCR first on the VDJ),'cdr3.nt' by VDJ and VJ cdr3s as nucleotides, 'cdrh3.nt.' by VDJ cdr3s as nucleotides, 'absolut' will match the VDJ_cdr3s_aa with the CDR3 column in Absolut! datasets. |
matching.type |
string, either 'exact' for exact sequence matching if the match.by parameter is a sequence type, or 'homology' for homology matching (matches if the Levehnstein distance is less than the distance.threshold parameter). |
distance.threshold |
integer, maximum string distance value by which to match sequences in the antigen data and sequences in the VDJ object (to further integrate the antigen data). |
cores |
Number of cores to use for parallel computations. Defaults to number of available cores. Setting this parameter is good practice on clusters. |
sample.id |
boolean, if T then will also match by the 'sample_id' column in the antigen dataframes. |
aberrant.chosen.sequences |
boolean, if T will add a column of the chosen aberrant sequences (which matched a sequence in the antigen data) if matching by sequence (and VDJ.VJ.1chain=F). |
output.format |
string, 'vgm' - returns the full VDJ object, 'dataframe.per.sample' - list of VDJ dataframes for each sample. |
Either the original VDJ dataframe with additional columns of the antigen features integrated, a list of VDJ dataframes per sample.
try({
VDJ_antigen_integrate(VDJ,antigen.directory.list=antigen.directory.list,
antigen.feature=c('elisa', 'affinity'),VDJ.VJ.1chain=T,
match.by='clonotype',sample.id=T, output.format='vgm')
})
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