sparrow

sparrow (Sequence PARameters for RegiOns in Windows) is a lightweight, object-oriented toolkit for analyzing and predicting features of protein sequences – with a particular focus on intrinsically disordered regions (IDRs).

What is sparrow?

Everything in sparrow hangs off a single Protein object: you create one from a sequence and then read parameters, properties, and predictions directly off it. Calculations are lazy and cached, so a Protein is cheap to make and you only compute what you ask for.

from sparrow import Protein

p = Protein("MEEEKKKKSSSTTTDDDQQQQNNNN")
p.FCR                          # fraction of charged residues
p.kappa                        # charge patterning
p.predictor.disorder()         # per-residue disorder prediction
p.predictor.radius_of_gyration()   # ALBATROSS Rg

What can it do?

  • Sequence parameters – composition, charge (FCR, NCPR, kappa, SCD), hydrophobicity, complexity, residue clustering and patches.

  • Linear profiles – per-residue windowed tracks for any of the above, plus 500+ published amino-acid property scales (AAindex).

  • Deep-learning predictions (via Protein.predictor) – disorder and pLDDT, DSSP secondary structure, polymer dimensions (Rg, Re, scaling exponent, asphericity), phosphorylation, localization signals, transactivation domains, transmembrane regions, and phase-separation propensity. These use the ALBATROSS networks and related PARROT-trained models.

  • Polymer-model properties (via Protein.polymeric) – analytical and simulation-derived dimensions and distance distributions.

  • Scale-up tools – batch prediction over whole sequence sets, and fixed-length feature vectors for machine learning.

Where to start

  • Installation – set up an environment and install sparrow.

  • Worked Examples – runnable walkthroughs (including plotting a linear NCPR profile).

  • The Protein Object – the complete, organized reference for everything you can do with a protein.

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