Proteomic profiling dataset of chemical perturbations in multiple biological backgrounds
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 340...
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Published in | Scientific data Vol. 8; no. 1; pp. 226 - 10 |
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Main Authors | , , , , , , , , , , , , , , , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
London
Nature Publishing Group UK
25.08.2021
Nature Publishing Group Nature Portfolio |
Subjects | |
Online Access | Get full text |
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Summary: | 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
https://clue.io/proteomics
.
Measurement(s)
drug perturbation response
Technology Type(s)
proteomic profiling
Factor Type(s)
cell line • drug
Sample Characteristic - Organism
Homo sapiens
Machine-accessible metadata file describing the reported data:
https://doi.org/10.6084/m9.figshare.14744064 |
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ISSN: | 2052-4463 2052-4463 |
DOI: | 10.1038/s41597-021-01008-4 |