Cargando…
ANPELA: Significantly Enhanced Quantification Tool for Cytometry‐Based Single‐Cell Proteomics
ANPELA is widely used for quantifying traditional bulk proteomic data. Recently, there is a clear shift from bulk proteomics to the single‐cell ones (SCP), for which powerful cytometry techniques demonstrate the fantastic capacity of capturing cellular heterogeneity that is completely overlooked by...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10214264/ https://www.ncbi.nlm.nih.gov/pubmed/36950745 http://dx.doi.org/10.1002/advs.202207061 |
_version_ | 1785047802587381760 |
---|---|
author | Zhang, Ying Sun, Huaicheng Lian, Xichen Tang, Jing Zhu, Feng |
author_facet | Zhang, Ying Sun, Huaicheng Lian, Xichen Tang, Jing Zhu, Feng |
author_sort | Zhang, Ying |
collection | PubMed |
description | ANPELA is widely used for quantifying traditional bulk proteomic data. Recently, there is a clear shift from bulk proteomics to the single‐cell ones (SCP), for which powerful cytometry techniques demonstrate the fantastic capacity of capturing cellular heterogeneity that is completely overlooked by traditional bulk profiling. However, the in‐depth and high‐quality quantification of SCP data is still challenging and severely affected by the large numbers of quantification workflows and extreme performance dependence on the studied datasets. In other words, the proper selection of well‐performing workflow(s) for any studied dataset is elusory, and it is urgently needed to have a significantly enhanced and accelerated tool to address this issue. However, no such tool is developed yet. Herein, ANPELA is therefore updated to its 2.0 version (https://idrblab.org/anpela/), which is unique in providing the most comprehensive set of quantification alternatives (>1000 workflows) among all existing tools, enabling systematic performance evaluation from multiple perspectives based on machine learning, and identifying the optimal workflow(s) using overall performance ranking together with the parallel computation. Extensive validation on different benchmark datasets and representative application scenarios suggest the great application potential of ANPELA in current SCP research for gaining more accurate and reliable biological insights. |
format | Online Article Text |
id | pubmed-10214264 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-102142642023-05-27 ANPELA: Significantly Enhanced Quantification Tool for Cytometry‐Based Single‐Cell Proteomics Zhang, Ying Sun, Huaicheng Lian, Xichen Tang, Jing Zhu, Feng Adv Sci (Weinh) Research Articles ANPELA is widely used for quantifying traditional bulk proteomic data. Recently, there is a clear shift from bulk proteomics to the single‐cell ones (SCP), for which powerful cytometry techniques demonstrate the fantastic capacity of capturing cellular heterogeneity that is completely overlooked by traditional bulk profiling. However, the in‐depth and high‐quality quantification of SCP data is still challenging and severely affected by the large numbers of quantification workflows and extreme performance dependence on the studied datasets. In other words, the proper selection of well‐performing workflow(s) for any studied dataset is elusory, and it is urgently needed to have a significantly enhanced and accelerated tool to address this issue. However, no such tool is developed yet. Herein, ANPELA is therefore updated to its 2.0 version (https://idrblab.org/anpela/), which is unique in providing the most comprehensive set of quantification alternatives (>1000 workflows) among all existing tools, enabling systematic performance evaluation from multiple perspectives based on machine learning, and identifying the optimal workflow(s) using overall performance ranking together with the parallel computation. Extensive validation on different benchmark datasets and representative application scenarios suggest the great application potential of ANPELA in current SCP research for gaining more accurate and reliable biological insights. John Wiley and Sons Inc. 2023-03-22 /pmc/articles/PMC10214264/ /pubmed/36950745 http://dx.doi.org/10.1002/advs.202207061 Text en © 2023 The Authors. Advanced Science published by Wiley‐VCH GmbH https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Articles Zhang, Ying Sun, Huaicheng Lian, Xichen Tang, Jing Zhu, Feng ANPELA: Significantly Enhanced Quantification Tool for Cytometry‐Based Single‐Cell Proteomics |
title | ANPELA: Significantly Enhanced Quantification Tool for Cytometry‐Based Single‐Cell Proteomics |
title_full | ANPELA: Significantly Enhanced Quantification Tool for Cytometry‐Based Single‐Cell Proteomics |
title_fullStr | ANPELA: Significantly Enhanced Quantification Tool for Cytometry‐Based Single‐Cell Proteomics |
title_full_unstemmed | ANPELA: Significantly Enhanced Quantification Tool for Cytometry‐Based Single‐Cell Proteomics |
title_short | ANPELA: Significantly Enhanced Quantification Tool for Cytometry‐Based Single‐Cell Proteomics |
title_sort | anpela: significantly enhanced quantification tool for cytometry‐based single‐cell proteomics |
topic | Research Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10214264/ https://www.ncbi.nlm.nih.gov/pubmed/36950745 http://dx.doi.org/10.1002/advs.202207061 |
work_keys_str_mv | AT zhangying anpelasignificantlyenhancedquantificationtoolforcytometrybasedsinglecellproteomics AT sunhuaicheng anpelasignificantlyenhancedquantificationtoolforcytometrybasedsinglecellproteomics AT lianxichen anpelasignificantlyenhancedquantificationtoolforcytometrybasedsinglecellproteomics AT tangjing anpelasignificantlyenhancedquantificationtoolforcytometrybasedsinglecellproteomics AT zhufeng anpelasignificantlyenhancedquantificationtoolforcytometrybasedsinglecellproteomics |