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Replication of single-cell proteomics data reveals important computational challenges.
Vanderaa, Christophe; Gatto, Laurent.
Afiliação
  • Vanderaa C; Computational Biology and Bioinformatics Unit (CBIO), de Duve Institute, UCLouvain, Belgium.
  • Gatto L; Computational Biology and Bioinformatics Unit (CBIO), de Duve Institute, UCLouvain, Belgium.
Expert Rev Proteomics ; 18(10): 835-843, 2021 10.
Article em En | MEDLINE | ID: mdl-34602016
ABSTRACT

INTRODUCTION:

Mass spectrometry-based proteomics is actively embracing quantitative, single-cell level analyses. Indeed, recent advances in sample preparation and mass spectrometry (MS) have enabled the emergence of quantitative MS-based single-cell proteomics (SCP). While exciting and promising, SCP still has many rough edges. The current analysis workflows are custom and built from scratch. The field is therefore craving for standardized software that promotes principled and reproducible SCP data analyses. AREAS COVERED This special report is the first step toward the formalization and standardization of SCP data analysis. scp, the software that accompanies this work, successfully replicates one of the landmark SCP studies and is applicable to other experiments and designs. We created a repository containing the replicated workflow with comprehensive documentation in order to favor further dissemination and improvements of SCP data analyses. EXPERT OPINION Replicating SCP data analyses uncovers important challenges in SCP data analysis. We describe two such challenges in detail batch correction and data missingness. We provide the current state-of-the-art and illustrate the associated limitations. We also highlight the intimate dependence that exists between batch effects and data missingness and offer avenues for dealing with these exciting challenges.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Software / Proteômica Idioma: En Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Software / Proteômica Idioma: En Ano de publicação: 2021 Tipo de documento: Article