Annotate TCR/BCR sequences using IgBLAST and MMseqs2 reference databases.
npx skills add https://github.com/antigenomics/arda --skill arda
Please help me install this Agent Skill. Skill: arda Source: https://github.com/antigenomics/arda/tree/main/skills/arda Command: npx skills add https://github.com/antigenomics/arda --skill arda
This Skill solves the problem of accurately and efficiently annotating TCR and BCR sequences, providing framework/CDR regions, V/D/J gene calls, constant-region isotype, junction/CDR3 boundaries, and AIRR output for both nucleotide and amino-acid inputs.
Use the arda skill to annotate TCR sequences from a bulk RNA-seq experiment.
High-intent search queries and answers about installing and using this skill.
TCR and BCR annotation identifies framework/CDR regions, V/D/J gene calls, and constant-region isotypes by mapping sequences to a pre-aligned reference database. This process provides junction/CDR3 boundaries and AIRR output for nucleotide and amino-acid inputs.
The fastest way to get V/D/J gene calls and CDR3 boundaries is using MMseqs2 to map sequences against a pre-aligned reference database. This bypasses expensive online IgBLAST computations, rapidly delivering junction details and AIRR-formatted output.
Yes, you can use IgBLAST for TCR annotation offline by performing the expensive alignment work beforehand to build a pre-aligned reference database. You then map your sequences to this database using MMseqs2 for fast annotation.
Yes, Python 3.10+ and the arda-mappers package are required to perform BCR annotation with this Skill. These dependencies are necessary to map sequences to the reference database and generate the annotated AIRR output.
Yes, this TCR annotation tool accepts both nucleotide and amino-acid inputs. It maps the provided sequences to the reference database to provide framework/CDR regions, junction/CDR3 boundaries, and constant-region isotypes.
Using MMseqs2 instead of IgBLAST directly for immune receptor annotation avoids the expensive IgBLAST runtime by mapping sequences to a pre-aligned reference. This delivers rapid V/D/J gene calls and CDR3 boundaries while maintaining annotation accuracy.
omicverseConverts bulk RNA-seq FASTQ or SRA inputs into gene-level count matrices.
KetomihineStructure best-practice workflows for single-cell AIRR analysis with Python packages.
danilomongeRuns nf-core/airrflow immune-repertoire analysis from raw reads or assembled data.
joyce820309Compare baseline and current web performance metrics to detect regressions.
