ting - T cell receptor interaction grouping
Project description
ting - T cell receptor interaction grouping
ting is a tool for clustering large scale T cell receptor repertoires by antigen-specificity
Synopsis
ting [options] -t sample.tsv -r reference.tsv -k kmer.tsv -o output.tsv
Options
Required Input
The user must provide a list of CDR3b sequences.
For compatibility reasons the tab seperated table of TCR sequences required for gliph is supported, too.
--tcr_sequences tcr_sequences The format of the table is tab delimited, expecting only the first
column. The header is optional, but if included only use column
names as shown in the example.
--kmer_file K-MER_FILE The k-mer file holds all 2-, 3- and 4-mers considered for local
clustering. If file does not exist it will automatically be
generated.
--reference Reference file of naive CDR3 amino acid sequences in fasta-format.
Used as control set by Fisher's exact test.
Example:
CDR3b TRBV TRBJ CDR3a TRAV TRAJ Sample-ID
CAADTSSGANVLTF TRBV30 TRBJ2-6 CALSDEDTGRRALTF TRAV19 TRAJ5 09/02171
CAATGGDRAYEQYF TRBV2 TRBJ2-7 CAASSGANSKLTF TRAV13-1 TRAJ56 03/04922
CAATQQGETQYF TRBV2 TRBJ2-5 CAASYGGSARQLTF TRAV13-1 TRAJ22 02/02591
CACVSNTEAFF TRBV28 TRBJ1-1 CAGDLNGAGSYQLTF TRAV25 TRAJ28 PBMC8631
CAGGKGNSPLHF TRBV2 TRBJ1-6 CVVLRGGSQGNLIF TRAV12-1 TRAJ42 02/02071
CAGQILAGSDTQYF TRBV6-4 TRBJ2-3 CATASGNTPLVF TRAV17 TRAJ29 09/00181
CAGRTGVSTDTQYF TRBV5-1 TRBJ2-3 CAVTPGGGADGLTF TRAV41 TRAJ45 02/02591
CAGYTGRANYGYTF TRBV2 TRBJ1-2 CVVNGGFGNVLHC TRAV12-1 TRAJ35 01/08733
Optional Input
--use_structural_boundaries If set, the first and last three amino acids will be included
in kmer counting and global clustering.
--no_global No global clustering will be performed.
--no_local No local clustering will be performed.
--min_kmer_occurence Only kmers which occure at least min_kmer_occurences times in the
sequence sample set will be taken in account. Default is 3.
--max_p_value p-value threshold for identifying significant motifs by fisher exact test
--gliph_minp probability threshold for identifying significant motifs by gliph test
--stringent_filtering Only TCRs starting with a cystein and ending with phenylalanine will be
used (IGMT definition of CDR3 region). Default: False
--kmers_gliph If set kmers are identified by the non-deterministic approach as implemented by gliph
Install
ting can be run from source or installed via PyPI or bioconda
PiPI:
pip install bio-ting
conda:
conda install -c bioconda bio-ting
Example
Example repertoires can be obtained from repertoires.tar.gz
included in the example_data
-folder
References have been created by the authors of gliph (Glanville et al.).
ting --tcr_sequences R205-L01-D704D504.tsv --reference reference.fasta --kmer_file R205-L01-D704D504_kmers.tsv -o R205-L01-D704D504_results.tsv
Project details
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