MPRAnalyze: statistical framework for massively parallel reporter assays.

MPRAnalyze: statistical framework for massively parallel reporter assays.

Ashuach, Tal;Fischer, David S;Kreimer, Anat;Ahituv, Nadav;Theis, Fabian J;Yosef, Nir;
Genome biology 2019 Vol. 20 pp. 183
299
ashuach2019mpranalyzegenome

Abstract

Massively parallel reporter assays (MPRAs) can measure the regulatory function of thousands of DNA sequences in a single experiment. Despite growing popularity, MPRA studies are limited by a lack of a unified framework for analyzing the resulting data. Here we present MPRAnalyze: a statistical framework for analyzing MPRA count data. Our model leverages the unique structure of MPRA data to quantify the function of regulatory sequences, compare sequences' activity across different conditions, and provide necessary flexibility in an evolving field. We demonstrate the accuracy and applicability of MPRAnalyze on simulated and published data and compare it with existing methods.

Citation

ID: 34613
Ref Key: ashuach2019mpranalyzegenome
Use this key to autocite in SciMatic or Thesis Manager

References

Blockchain Verification

Account:
NFT Contract Address:
0x95644003c57E6F55A65596E3D9Eac6813e3566dA
Article ID:
34613
Unique Identifier:
10.1186/s13059-019-1787-z
Network:
Scimatic Chain (ID: 481)
Loading...
Blockchain Readiness Checklist
Authors
Abstract
Journal Name
Year
Title
5/5
Creates 1,000,000 NFT tokens for this article
Token Features:
  • ERC-1155 Standard NFT
  • 1 Million Supply per Article
  • Transferable via MetaMask
  • Permanent Blockchain Record
Blockchain QR Code
Scan with Saymatik Web3.0 Wallet

Saymatik Web3.0 Wallet