Pyrepseq: the Swiss army knife of immune repertoire analyses

Our adaptive immune system employs an amazingly diverse cast of specific cells to maintain host homeostasis in the face of pathogens and other disturbances. A census of a person’s T cells or B cells can be obtained by sequencing the genomic regions coding for the hypervariable receptors of these cells. pyrepseq is a Python library to reveal patterns in the complex datasets resulting from such so-called immune repertoire sequencing.

Pyrepseq aims to be the scipy & seaborn for studying adaptive immunity: modular implementations of algorithms for fast analyses, and bespoke plotting functions for compelling visualizations.

Documentation

You can install pyrepseq using pip:

pip install pyrepseq

For API documentation see below:

• API Reference
  • main module
    • IO
      • isvalidaa()
      • isvalidcdr3()
      • multimerge()
      • standardize_dataframe()
    • Stats
      • chao1()
      • jaccard_index()
      • overlap()
      • overlap_coefficient()
      • pc()
      • pc_n()
      • powerlaw_mle_alpha()
      • powerlaw_sample()
      • stdpc()
      • stdpc_n()
      • var_chao1()
      • varpc_n()
    • Distance
      • calculate_neighbor_numbers()
      • cdist()
      • downsample()
      • find_neighbor_pairs()
      • find_neighbor_pairs_index()
      • hamming_neighbors()
      • hierarchical_clustering()
      • isdist1()
      • levenshtein_neighbors()
      • load_pcDelta_background()
      • next_nearest_neighbors()
      • nndist_hamming()
      • pcDelta()
      • pcDelta_grouped()
      • pcDelta_grouped_cross()
      • pdist()
  • plotting submodule
    • align_seqs()
    • label_axes()
    • labels_to_colors_hls()
    • labels_to_colors_tableau()
    • rankfrequency()
    • seqlogos()
    • seqlogos_vj()
    • similarity_clustermap()