Replication of single-cell proteomics data reveals important computational challenges

Abstract

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 build from scratch. The field is therefore craving for standardized software that promotes principled and reproducible SCP data analyses. This special report represents the first step toward the formalization of standard SCP data analysis. scp, the software that accompanies this work can successfully reproduces one of the landmark data in the field of SCP. We created a repository containing the reproduction workflow with comprehensive documentation in order to favor further dissemination and improvement of SCP data analyses.Reproducing 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 highlights the intimate dependence that exists between batch effects and data missingness and provides future tracks for dealing with these exciting challenges.

Multiplexed single-cell proteomics using SCoPE2

“…Below we describe data analysis that can be implemented using the SCoPE2 GitHub [51] or Zendo [52] repositories. This SCoPE2 code was used to develop the scp Bioconductor package [53,54], which can also be used to analyze the data.…”

Single Cell Proteomics Using a Trapped Ion Mobility Time-of-Flight Mass Spectrometer Provides Insight into the Post-translational Modification Landscape of Individual Human Cells

“…Single cell proteomics is a newly emerging field with tremendous promise as a complementary technology to both proteomics and other single cell technologies. The majority of studies described to date have necessarily focused on developing the sample preparation, 6,9,25 instrument methods 43,44 and informatics tools 29,45,46 necessary to lay the groundwork for later applications. Much of this valuable development has been performed using diluted bulk proteomics samples 13 , frog embryos 47 , or clonal populations of hundreds of cells harvested from single cell seeding 48 or laser capture microdissection.…”

Quantitative Accuracy and Precision in Multiplexed Single-Cell Proteomics

“… 23 The need for quantitative data imputation in standard single-cell DDA data is highly elevated compared to standard input, while the absence of technical replicates challenges the reliability. 11 , 20 , 37 − 39 Despite the intentional coisolation in DIA-TMT, eliminating precursor stochasticity drastically improved both the accuracy and the sensitivity ( Figure 4 b–f). 23 Hence, we speculate that large proportions of computationally generated quantitative data introduced by reduced replicate overlap in combination with precursor coisolation and extreme carrier ratios are particularly error prone.…”