Evidence map›Paper›PMID 41102581›Full record

ReviewNature protocols2026

Navigating the data processing for cytometry-based single-cell proteomics.

Huaicheng Sun, Yuan Zhou, Ruoyu Jiang, Yuxuan Liu, Chengbin Gu, Ziqi Pan, Minjie Mou, Xichen Lian, Bohan Chen, Tianle Niu and 15 more

Abstract readReview
PubMed Publisher
In one paragraph

Review in Nature protocols, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

25 authors.

Huaicheng Sun *College of Pharmaceutical Sciences, National Key Laboratory of Advanced Drug Delivery and Release Systems, Zhejiang University, Hangzhou, China.ORCID 0000-0002-1381-9571
Yuan Zhou *College of Pharmaceutical Sciences, National Key Laboratory of Advanced Drug Delivery and Release Systems, Zhejiang University, Hangzhou, China.
Ruoyu Jiang *College of Pharmaceutical Sciences, National Key Laboratory of Advanced Drug Delivery and Release Systems, Zhejiang University, Hangzhou, China.
Yuxuan LiuDepartment of Otolaryngology Head and Neck Surgery, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Chengbin GuZhejiang University-University of Edinburgh Institute, Zhejiang University School of Medicine, Haining, China.
Ziqi PanCollege of Pharmaceutical Sciences, National Key Laboratory of Advanced Drug Delivery and Release Systems, Zhejiang University, Hangzhou, China.
Minjie MouCollege of Pharmaceutical Sciences, National Key Laboratory of Advanced Drug Delivery and Release Systems, Zhejiang University, Hangzhou, China.
Xichen LianCollege of Pharmaceutical Sciences, National Key Laboratory of Advanced Drug Delivery and Release Systems, Zhejiang University, Hangzhou, China.
Bohan ChenCollege of Life Sciences, Zhejiang University, Hangzhou, China.
Tianle NiuSchool of Pharmacy, Hebei Medical University, Shijiazhuang, China.
Ying ZhangCollege of Pharmaceutical Sciences, National Key Laboratory of Advanced Drug Delivery and Release Systems, Zhejiang University, Hangzhou, China.
Yintao ZhangCollege of Pharmaceutical Sciences, National Key Laboratory of Advanced Drug Delivery and Release Systems, Zhejiang University, Hangzhou, China.ORCID 0000-0002-5263-3438
Baoliang ZhangDepartment of Intelligent Medical Engineering, School of Biomedical Engineering, Anhui Medical University, Hefei, China.
Xiuna SunDepartment of Otolaryngology Head and Neck Surgery, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Hao YangSchool of Pharmacy, Hebei Medical University, Shijiazhuang, China.
Xin ShenCollege of Pharmaceutical Sciences, National Key Laboratory of Advanced Drug Delivery and Release Systems, Zhejiang University, Hangzhou, China.
Yangbo DaiState Key Laboratory for Organic Electronics and Information Displays, Institute of Advanced Materials, Nanjing University of Posts and Telecommunications, Nanjing, China.
Jiannan DengCollege of Pharmaceutical Sciences, National Key Laboratory of Advanced Drug Delivery and Release Systems, Zhejiang University, Hangzhou, China.
Siqi LiuChu Kochen Honors College, Zhejiang University, Hangzhou, China.
Yang ZhangSchool of Pharmacy, Hebei Medical University, Shijiazhuang, China.
Mang XiaoDepartment of Otolaryngology Head and Neck Surgery, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Wanqing XieDepartment of Intelligent Medical Engineering, School of Biomedical Engineering, Anhui Medical University, Hefei, China.
Qingxia YangZhejiang Provincial Key Laboratory of Precision Diagnosis and Therapy for Major Gynecological Diseases, Women's Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Tingting FuCollege of Pharmaceutical Sciences, National Key Laboratory of Advanced Drug Delivery and Release Systems, Zhejiang University, Hangzhou, China. futt@zju.edu.cn.ORCID 0009-0007-6486-2426
Feng ZhuCollege of Pharmaceutical Sciences, National Key Laboratory of Advanced Drug Delivery and Release Systems, Zhejiang University, Hangzhou, China. zhufeng@zju.edu.cn.ORCID 0000-0001-8069-0053

Funding

National Key R&D Programs of ChinaNational Natural Science Foundation of China (National Science Foundation of China) 22220102001Natural Science Foundation of Zhejiang
6 · The paper itself

Abstract

Cytometry-based single-cell proteomics (SCP) has emerged as a powerful technique that greatly advances our understanding of complex biological systems with a new level of granularity. Various methods have been developed to process cytometry-based SCP data. However, it remains extremely challenging to identify the well-performing processing workflows for specific datasets. Here, we develop ANPELA, an out-of-the-box method for navigating the proteomic data processing based on large-scale screening. It enables a comparison among the performances of thousands of the processing workflows in identifying cell subpopulations and inferring pseudo-time trajectories based on machine learning. Several cases are then analyzed, highlighting its ability to identify the optimal ways of data processing for cytometry-based SCP studies. A new package is also deployed to ensure multiscenario usability (such as desktop software, R package and online server), data security (enabling local and open-source execution) and a user-friendly interface (realizing interactive and visualizable applications). Overall, ANPELA can be utilized by a broad audience, including those without coding skills, and is freely accessible and downloadable at https://idrblab.org/anpela/ . Its execution time may range from minutes to hours depending on the size of the analyzed data.

Indexed as

Flow CytometryProteomicsSingle-Cell AnalysisHumansMachine LearningSoftwareWorkflow

Identifiers

PMID41102581

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.