RPPA SPACE: an R package for normalization and quantitation of Reverse-Phase Protein Array data

Huma Shehwana, Shwetha V. Kumar, James M. Melott, Mary A. Rohrdanz, Chris Wakefield, Zhenlin Ju, Doris R. Siwak, Yiling Lu, Bradley M. Broom, John N. Weinstein, Gordon B. Mills, Rehan Akbani

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Reverse-Phase Protein Array (RPPA) is a robust high-throughput, cost-effective platform for quantitatively measuring proteins in biological specimens. However, converting raw RPPA data into normalized, analysis-ready data remains a challenging task. Here, we present the RPPA SPACE (RPPA Superposition Analysis and Concentration Evaluation) R package, a substantially improved successor to SuperCurve, to meet that challenge. SuperCurve has been used to normalize over 170 000 samples to date. RPPA SPACE allows exclusion of poor-quality samples from the normalization process to improve the quality of the remaining samples. It also features a novel quality-control metric, ‘noise’, that estimates the level of random errors present in each RPPA slide. The noise metric can help to determine the quality and reliability of the data. In addition, RPPA SPACE has simpler input requirements and is more flexible than SuperCurve, it is much faster with greatly improved error reporting.

Original languageEnglish (US)
Pages (from-to)5131-5133
Number of pages3
JournalBioinformatics
Volume38
Issue number22
DOIs
StatePublished - Nov 15 2022

ASJC Scopus subject areas

  • Statistics and Probability
  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Computational Theory and Mathematics
  • Computational Mathematics

Fingerprint

Dive into the research topics of 'RPPA SPACE: an R package for normalization and quantitation of Reverse-Phase Protein Array data'. Together they form a unique fingerprint.

Cite this