PoolParty: streamlined design of DNA sequence libraries in Python.
- 1Simons Center for Quantitative Biology, Cold Spring Harbor Laboratory, 1 Bungtown Rd., Cold Spring Harbor, New York, 11724, USA.
- 2Simons Center for Quantitative Biology, Cold Spring Harbor Laboratory, 1 Bungtown Rd., Cold Spring Harbor, New York, 11724, USA. [email protected].
Abstract
Background
Computationally designed DNA sequence libraries are essential components of massively parallel reporter assays (MPRAs), deep mutational scanning (DMS) experiments, and other multiplex assays of variant effect (MAVEs). They are also increasingly used in silico to analyze genomic AI models. Designing these libraries, however, remains tedious and error-prone due to the scarcity of purpose-built software.Results
Here we describe PoolParty, a Python package that streamlines the design of complex oligo pools using a simple but flexible API. In PoolParty, each library is represented by a computational graph that can be specified in just a few lines of code. Over 50 built-in operations cover nucleotide- and codon-level mutagenesis, motif insertion, barcode generation, and more. PoolParty automatically generates informative names for each sequence and provides "design cards" detailing how each sequence was generated. Visualization methods let users quickly audit library content and inspect the underlying graph. PoolParty thus transforms oligo pool design from a tedious task requiring custom functions and scripts into a structured, transparent, and reproducible process.Conclusions
PoolParty streamlines the design of DMS, MPRA, and other multiplex assay libraries, and the design cards it provides can help researchers systematically probe and interpret genomic AI models. PoolParty can also be extended to support new assays and analysis strategies as they emerge.
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BibTeX
@article{liu2026poolparty,
title = {{PoolParty: streamlined design of DNA sequence libraries in Python.}},
author = {Zhihan Liu and Aidan Cordero and Justin B Kinney},
journal = {BMC bioinformatics},
year = {2026},
month = oct,
doi = {10.1186/s12859-026-06696-6},
url = {https://europepmc.org/article/MED/42963559},
note = {CC BY-NC-ND},
}
RIS
TY - JOUR
TI - PoolParty: streamlined design of DNA sequence libraries in Python.
AU - Zhihan Liu
AU - Aidan Cordero
AU - Justin B Kinney
PY - 2026
DA - 2026/10/30
JO - BMC bioinformatics
DO - 10.1186/s12859-026-06696-6
UR - https://europepmc.org/article/MED/42963559
AB - Background Computationally designed DNA sequence libraries are essential components of massively parallel reporter assays (MPRAs), deep mutational scanning (DMS) experiments, and other multiplex assays of variant effect (MAVEs). They are also increasingly used in silico to analyze genomic AI models. Designing these libraries, however, remains tedious and error-prone due to the scarcity of purpose-built software.Results Here we describe PoolParty, a Python package that streamlines the design of complex oligo pools using a simple but flexible API. In PoolParty, each library is represented by a computational graph that can be specified in just a few lines of code. Over 50 built-in operations cover nucleotide- and codon-level mutagenesis, motif insertion, barcode generation, and more. PoolParty automatically generates informative names for each sequence and provides "design cards" detailing how each sequence was generated. Visualization methods let users quickly audit library content and inspect the underlying graph. PoolParty thus transforms oligo pool design from a tedious task requiring custom functions and scripts into a structured, transparent, and reproducible process.Conclusions PoolParty streamlines the design of DMS, MPRA, and other multiplex assay libraries, and the design cards it provides can help researchers systematically probe and interpret genomic AI models. PoolParty can also be extended to support new assays and analysis strategies as they emerge.
SN - 1471-2105
ER -