数据收集-分化轨迹推断

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1

参考

Ranek, J.S., Stanley, N. & Purvis, J.E. Integrating temporal single-cell gene expression modalities for trajectory inference and disease prediction. Genome Biol 23, 186 (2022). https://doi.org/10.1186/s13059-022-02749-0

内容

The raw publicly available single-cell RNA sequencing datasets downloaded and used in this study are available in the
Gene Expression Omnibus (GEO; https://www.ncbi.nlm.nih.gov/geo/) repository, under the accession codes GSE81682
for hematopoiesis diferentiation (Nestorowa) [86]; GSE74596 for NKT cell diferentiation [87]; GSE70236, GSE70240,
and GSE70244 for hematopoiesis diferentiation (Olsson) [88]; GSE94383 for LPS stimulation [89]; GSE161465 for INFγ
stimulation [90]; GSE116481 for AML chemotherapy [91]; GSE126068 for AML diagnosis/relapse [92]; and GSE138266 for MS case/control PBMC and CSF datasets [93] and in the European Nucleotide Archive (ENA; https://www.ebi.ac.uk/arrayexpress/experiments/) repository, under accession numbers E-MTAB-2805 for mouse embryonic cell cycle [94] datasets, respectively. Loom fles and preprocessed data are available in the Zenodo repository https://doi.org/10.5281/zenodo.6587903 [95]. Source code including all functions for preprocessing, integration, and evaluation are publicly available at www.github.com/jranek/EVI [96] and in the Zenodo repository [97].

2

参考

Saelens, W., Cannoodt, R., Todorov, H. et al. A comparison of single-cell trajectory inference methods. Nat Biotechnol 37, 547–554 (2019). https://doi.org/10.1038/s41587-019-0071-9

内容

The scripts to download and process these datasets are available on our repository (https://benchmark.dynverse.org/tree/master/scripts/01-datasets).

3

参考

Wolf, F. & Hamey, Fiona & Plass, Mireya & Solana, Jordi & Dahlin, Joakim & Rajewsky, Nikolaus & Simon, Lukas & Theis, Fabian. (2019). PAGA: graph abstraction reconciles clustering with trajectory inference through a topology preserving map of single cells. Genome biology. 20. 10.1186/s13059-019-1663-x.

内容

4

参考

Zeng, Y., He, J., Bai, Z. et al. Tracing the first hematopoietic stem cell generation in human embryo by single-cell RNA sequencing. Cell Res 29, 881–894 (2019). https://doi.org/10.1038/s41422-019-0228-6

内容

The scRNA-seq data reported in this study have been deposited in NCBI’s Gene Expression Omnibus (GEO) with the accession number GSE135202. All other relevant data in this study are available from the corresponding authors upon reasonable request.

5

参考

Junjie Du, Han He, Zongcheng Li, Jian He, Zhijie Bai, Bing Liu, Yu Lan,
Integrative transcriptomic analysis of developing hematopoietic stem cells in human and mouse at single-cell resolution,
Biochemical and Biophysical Research Communications,Volume 558,2021,Pages 161-167,ISSN 0006-291X,

内容

2.1.1. Mouse
Zhou et al. performed single-cell transcriptome sequencing on cells during the development of HSCs [3]. Expression matrix of cell populations (type 1 and 2 pre-HSCs, E12/E14 HSCs and adult HSCs, abbreviated as mT1 and mT2 pre-HSCs, mE12/mE14 HSCs and mAdult HSC respectively) was downloaded from GEO database (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE67120).

Hou et al. constructed high-precision single-cell transcriptomics to unbiasedly examine the endothelial cells populations at continuous developmental stages with intervals of 0.5 days from embryonic day (E) 9.5 to E11.0 [4]. Expression matrix of cell populations (HECs, type 1 pre-HSCs, abbreviated as mHECs and mT1 pre-HSCs respectively) was downloaded from: https://github.com/Liu-Lan-lab/Project_mHEC_CR2020.

2.1.2. Human
Zeng et al. analyzed the cell populations of the dorsal aorta during the temporal window of human embryonic HSC generation using single-cell transcriptome sequencing [6]. Expression matrix of cell populations (HECs, three subsets of HSPCs, abbreviated as hHECs and hHSPC_GJA5+/Cycling/GFI1B+, respectively) was downloaded from: https://github.com/Liu-Lan-lab/Project_hHEC_HSPC_CR2019.

Bian et al. applied scRNA-seq on CD45+ hematopoietic cell populations from a range of tissues in human embryos, and transcriptomically identified HSPCs with high expression of such as CD34, MYB, and HOX family transcription factors HOXA6 and HOXA10 in liver at CS20 and CS23 [9]. Expression matrix of HSPCs in human fetal liver (abbreviated as hHSPC_FL) was downloaded from: https://github.com/Liu-Lan-lab/human_macrophage_project_data

6：methods and datasets review

参考

Shen, Sophie et al. “Integrating single-cell genomics pipelines to discover mechanisms of stem cell differentiation.” Trends in molecular medicine vol. 27,12 (2021): 1135-1158. doi:10.1016/j.molmed.2021.09.006

内容

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