Guidelines for bioinformatics of single-cell sequencing data analysis in Alzheimer's disease: review, recommendation, implementation and application
Minghui Wang, Won-Min Song, Chen Ming, Qian Wang, Xianxiao Zhou, Peng Xu, Azra Krek, Yonejung Yoon et al.. Molecular neurodegeneration, 2022-03-02
Topic: Genetics and APOE
Alzheimer's disease (AD) is the most common form of dementia, characterized by progressive cognitive impairment and neurodegeneration. Extensive clinical and genomic studies have revealed biomarkers, risk factors, pathways, and targets of AD in the past decade. However, the exact molecular basis of AD development and progression remains elusive. The emerging single-cell sequencing technology can potentially provide cell-level insights into the disease. Here we systematically review the state-of-the-art bioinformatics approaches to analyze single-cell sequencing data and their applications to AD in 14 major directions, including 1) quality control and normalization, 2) dimension reduction and feature extraction, 3) cell clustering analysis, 4) cell type inference and annotation, 5) differential expression, 6) trajectory inference, 7) copy number variation analysis, 8) integration of single-cell multi-omics, 9) epigenomic analysis, 10) gene network inference, 11) prioritization of cell subpopulations, 12) integrative analysis of human and mouse sc-RNA-seq data, 13) spatial transcriptomics, and 14) comparison of single cell AD mouse model studies and single cell human AD studies. We also address challenges in using human postmortem and mouse tissues and outline future developments in single cell sequencing data analysis. Importantly, we have implemented our recommended workflow for each major analytic direction and applied them to a large single nucleus RNA-sequencing (snRNA-seq) dataset in AD. Key analytic results are reported while the scripts and the data are shared with the research community through GitHub. In summary, this comprehensive review provides insights into various approaches to analyze single cell sequencing data and offers specific guidelines for study design and a variety of analytic directions. The review and the accompanied software tools will serve as a valuable resource for studying cellular and molecular mechanisms of AD, other diseases, or biological systems at the single cell level.
Key findings
- Extensive clinical and genomic studies have revealed biomarkers, risk factors, pathways, and targets of AD in the past decade.
- Key analytic results are reported while the scripts and the data are shared with the research community through GitHub.
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Study details
- Evidence strengthLow
How this study scored 63/100
Published in a peer-reviewed journal, and it is a systematic review of all the studies on the question. Scored zero for sample size, effect reported and studied in people because the record does not state it. We have no data on journal's citation record, times cited, citations per year, impact for its field and year, cited by studies here, still being cited, senior author's track record, institution's track record, multi-centre collaboration and free to read, so those were left out: it earned 35 of the 56 points we could judge it on, which is 63 out of 100.
| Component | Points | Why |
|---|---|---|
| Journal tier | 7 / 10 | Tier 3 — peer-reviewed journal (Molecular neurodegeneration) |
| Journal's citation record | — / 4 | No journal record from OpenAlex — left out of this score |
| Study design | 12 / 12 | A systematic review of all the studies on the question (from PubMed type “Systematic Review”) |
| Strength of evidence | 1 / 5 | Rated “low” in our summary |
| Peer-review validation | 10 / 10 | Peer-reviewed. Published as an article in a named peer-reviewed journal. |
| How recent | 3 / 5 | 2022 — within 6 year(s) of the newest study here |
| Sample size | 0 / 4 | Participant count not stated — scores zero (not stated in the record — scored 0) |
| Effect reported | 0 / 3 | No effect size reported — scores zero (not stated in the record — scored 0) |
| Studied in people | 0 / 3 | Not stated whether this was studied in people — scores zero (not stated in the record — scored 0) |
| Randomised / blinded | 0 / 2 | A review of other studies — randomisation is not credited here |
| Times cited | — / 7 | No citation count (not found in OpenAlex) — left out of this score |
| Citations per year | — / 5 | No citation count or no year — left out of this score |
| Impact for its field and year | — / 6 | No field-weighted citation impact (OpenAlex has none yet) — left out of this score |
| Cited by studies here | — / 6 | Not yet checked against this library's citation graph — left out of this score |
| Still being cited | — / 4 | No yearly citation counts — left out of this score |
| Senior author's track record | — / 4 | Senior author's record not available — left out of this score |
| Institution's track record | — / 3 | No institution listed in OpenAlex — left out of this score |
| Multi-centre collaboration | — / 3 | Institutions not listed — left out of this score |
| Indexed in PubMed | 2 / 2 | Indexed in PubMed (PMID 35236372) |
| Free to read | — / 2 | Access not recorded — left out of this score |
| Points | 35 / 56 | Scored on 10 of 20 parts. We have no data for the rest, so they are left out: 35 of the 56 points we could judge it on is 63 out of 100. |
| Total | 63 / 100 | — |
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Cite this study APA, Vancouver, BibTeX · download .bib or .ris
Built from the record alzhub holds for this paper, not looked up. Volume, issue and page numbers are not held in the record. The record's author list ends in “et al.”, so not every author is named. Check the citation against the original before you use it.
APA 7th
Wang, M., Song, W.-M., Ming, C., Wang, Q., Zhou, X., Xu, P., et al. (2022). Guidelines for bioinformatics of single-cell sequencing data analysis in Alzheimer's disease: review, recommendation, implementation and application. Molecular neurodegeneration. https://doi.org/10.1186/s13024-022-00517-z
Vancouver
Wang M, Song W.-M, Ming C, Wang Q, Zhou X, Xu P, et al. Guidelines for bioinformatics of single-cell sequencing data analysis in Alzheimer's disease: review, recommendation, implementation and application. Molecular neurodegeneration. 2022. doi:10.1186/s13024-022-00517-z. PMID: 35236372.
BibTeX
@article{wang2022-35236372,
author = {Wang, Minghui and Song, Won-Min and Ming, Chen and Wang, Qian and Zhou, Xianxiao and Xu, Peng and Krek, Azra and Yoon, Yonejung and others},
title = {{Guidelines for bioinformatics of single-cell sequencing data analysis in Alzheimer's disease: review, recommendation, implementation and application}},
journal = {Molecular neurodegeneration},
year = {2022},
doi = {10.1186/s13024-022-00517-z},
pmid = {35236372},
url = {https://doi.org/10.1186/s13024-022-00517-z}
}
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