single-cell-genetics Popular repositoriesLoading cellsnp-litecellsnp-litePublic Efficient genotyping bi-allelic SNPs on single cells C12811 cellSNPcellSNPPublic Pileup biallelic SNPs from single-cell and bulk RNA-seq data Python7411 vireovireoPublic...
The article focuses on a study conducted by Chris Holmes, Quin Wills and colleagues on single-cell gene expression analysis. It discusses new methods of identification of the genomic variants that affect gene expression levels or expression quantitative trait loci (eQTL). It mentions that the study...
pip install -U git+https://github.com/single-cell-genetics/cellSNP In either case, if you don't have write permission for your current Python environment, we suggest creating a separateconda environmentor add--userfor your current one. ...
The generation of HypoMap To develop a unified hypothalamic cell atlas comprising cell types from major hypothalamic regions, we combined 17 publicly available droplet-based hypothalamus sc-seq datasets5,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41covering different hypothalamic regions, from ...
Cell by cell: population genetics in the wild Tanja Woyke highlights a 2014 study by Kashtan et al., who applied single-cell genomics to populations of the marine cyanobacteriumProchlorococcus, revealing hundreds of subpopulations with distinct genomic backbones of this wild uncultured microorganism. ...
Cellular heterogeneity is revolutionizing the way to study, monitor and dissect complex diseases. This has been possible with the technological and computational advances associated to single-cell genomics and epigenomics. Deeper understanding of cell-to-cell variation and its impact on tissue function wi...
Current methods for analyzing single-cell datasets have relied primarily on static gene expression measurements to characterize the molecular state of individual cells. However, capturing temporal changes in cell state is crucial for the interpretation of dynamic phenotypes such as the cell cycle, develop...
Nature Genetics:CRISPR Screen结合生化筛选获得功能基因 也很简单,就是gRNA侵染,然后按marker筛选Clone,然后做差异对比。比如抑制differentiation的gene KO应该富集在KRT20高表达的细胞里。 2023年02月27日 第一代perturb-seq:CROP-seq https://www.bocklab.org/resources/crop-seq ...
Journal:Nature Genetics(IF=30.8) 一句话简介 文章对多个脑区进行了bulk ATAC-seq,scATAC-seq和HiChIP,结合这些方法和基于机器学习的pipeline,对GWAS研究中的AD和PD相关SNP进行了筛选和功能推断,解释了已发现和未发现的风险基因中部分SNP的致病机制。 结果 ...
单细胞分析的主要目标是研究细胞之间的异同,揭示不同细胞之间的差异、相似性以及这些差异和相似性背后的原因。 而这些异同是可以从不同层面揭示的: DNA:基因组序列测量(genome sequence),染色质可访问性(chromatin accessibility),DNA甲基化(DNA methylation),组蛋白修饰(histone modifications),染色体构象(chromosomal conf...