Inferring cells differentiation processes from single-cell Multiome ATACseq+RNAseq data.

从单细胞 Multiome ATACseq RNAseq 数据推断细胞分化过程。

• 批准号: 22K21301
• 负责人: Loza Lopez.Martin.de.Jesus
• 金额: $ 1.83万
• 依托单位: The University of Tokyo
• 依托单位国家: 日本
• 项目类别: Grant-in-Aid for Research Activity Start-up
• 财政年份: 2022
• 资助国家: 日本
• 起止时间: 2022-08-31 至 2024-03-31
• 项目状态: 已结题
• 来源: https://kaken.nii.ac.jp/en/grant/KAKENHI-PROJECT-22K21301/
• 关键词: Bioinformatics; Cells-reprogramming; Multiomics; RNA-velocity; Single-cell; Cell-fate

I confirmed the significance of this project in terms of a recent method published in a high-impact factor journal.I set up the computational environment and worked on the estimation of gene expression levels of cells within clusters.I tested different linear methods with and without regularization terms. I conclude that estimation with regularization, especially the ridge regressor, was more appropriate for single-cell RNA-seq data as they reduce the impact of the high sparsity of the data.I set up the fuzzy logic interpolation. I performed different tests on the interpolation of the estimated cluster-specific gene dynamics with satisfactory results. With these tests, I was able to perform in-silico simulations of a cell differentiating from one cluster to another.

我通过最近发表在高影响因子期刊上的一种方法证实了这个项目的重要性。我建立了计算环境，并致力于估计簇内细胞的基因表达水平。我测试了不同的线性方法，包括有和没有正则化项。我的结论是，估计与正则化，特别是岭回归，是更适合单细胞RNA-seq数据，因为他们减少了数据的高稀疏性的影响。我建立了模糊逻辑插值。我进行了不同的测试插值估计集群特定的基因动态与满意的结果。通过这些测试，我能够对细胞从一个集群到另一个集群进行计算机模拟。

项目成果

Characterization of housekeeping enhancers and their targets in the human genome

人类基因组中管家增强子及其靶标的表征

• 发表时间: 2022
• 作者: K. Kawaharazuka;K. Okada;M. Inaba;Loza Martin
• 通讯作者: Loza Martin

Unbiased integration of single cell transcriptome replicates

• DOI: 10.1101/2021.05.05.442380
• 发表时间: 2021-05
• 期刊: NAR Genomics and Bioinformatics
• 影响因子: 4.6
• 作者: Martin Loza Lopez;Shunsuke Teraguchi;D. Standley;Diego Diez

Housekeeping enhancers in the human genome

人类基因组中的管家增强子

• 发表时间: 2022
• 作者: Y. Ribayashi;K. Kawaharazuka;Y. Toshimitsu;D. Kusuyama;A. Miki;K. Shinjo;M. Bando;T. Suzuki;Y. Kojio;K. Okada;M. Inaba;Loza Martin
• 通讯作者: Loza Martin