Proteomic profiling dataset of chemical perturbations in multiple biological backgrounds.

Sci Data
Authors
Abstract

While gene expression profiling has traditionally been the method of choice for large-scale perturbational profiling studies, proteomics has emerged as an effective tool in this context for directly monitoring cellular responses to perturbations. We previously reported a pilot library containing 3400 profiles of multiple perturbations across diverse cellular backgrounds in the reduced-representation phosphoproteome (P100) and chromatin space (Global Chromatin Profiling, GCP). Here, we expand our original dataset to include profiles from a new set of cardiotoxic compounds and from astrocytes, an additional neural cell model, totaling 5300 proteomic signatures. We describe filtering criteria and quality control metrics used to assess and validate the technical quality and reproducibility of our data. To demonstrate the power of the library, we present two case studies where data is queried using the concept of "connectivity" to obtain biological insight. All data presented in this study have been deposited to the ProteomeXchange Consortium with identifiers PXD017458 (P100) and PXD017459 (GCP) and can be queried at .

Year of Publication
2021
Journal
Sci Data
Volume
8
Issue
1
Pages
226
Date Published
2021 08 25
ISSN
2052-4463
DOI
10.1038/s41597-021-01008-4
PubMed ID
34433823
PubMed Central ID
PMC8387426
Links
Grant list
U24 CA210986 / CA / NCI NIH HHS / United States
U54-HG008097 / U.S. Department of Health & Human Services | NIH | National Human Genome Research Institute (NHGRI)
U54 HG008097 / HG / NHGRI NIH HHS / United States
U01 CA214125 / CA / NCI NIH HHS / United States
U01-CA214125 / U.S. Department of Health & Human Services | NIH | National Cancer Institute (NCI)
U24-CA210986 / U.S. Department of Health & Human Services | NIH | National Cancer Institute (NCI)