数据收集-分化轨迹推断

数据收集-分化轨迹推断

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

相关推荐
北京中科新远科技14 分钟前
兼容光模块上线前怎么测:识别、DOM、误码与批次回归清单
人工智能·数据挖掘·回归
SL_staff3 小时前
BI落地失败的3个技术断点:从数据接入、自助分析到服务闭环的工程实践
java·数据分析·数据可视化
ViperL14 小时前
[高光谱]DADnet-基于对抗生成的单源域泛化分类
人工智能·分类·数据挖掘
葫三生4 小时前
关于三生原理系列被技术开发社区批量收录或引发策展边界讨论的一种思考
大数据·人工智能·深度学习·算法·机器学习·数据挖掘·开源
Aloudata4 小时前
语义资产运营指南:如何管理指标、维度、口径、Owner、血缘和使用记录
数据库·人工智能·数据分析·数据资产·dataagent·语义层
跟我学机器学习6 小时前
拥有短期记忆的RAG Agent:记忆增强检索实战
人工智能·深度学习·语言模型·数据挖掘·rag
体验家7 小时前
智能家居AI+BI数据洞察:体验家如何连接设备运行与用户评价
数据分析·智能家居·客户体验管理
KEYSTONE_lucy7 小时前
海外仓维修系统架构与成本拆解:家具维修海外仓技术方案与价格对比
数据分析
镜舟科技7 小时前
镜舟科技 CTO 陈鹏:从实时分析到统一的数据分析与智能平台
starrocks·数据分析·镜舟科技·data agent·mip·统一数据·业务语义
Databend7 小时前
以云原生湖仓支撑 AI 应用落地丨Databend 亮相 2026 人工智能开放计算大会
大数据·数据库·数据分析