Project description:This is a droplet-based single cell transcriptome data set from 13 human fetal livers (6-18 PCW) and 8 skin and kidney samples (6-12 PCW). It includes 199,642 cells with a mean detected gene number of 3000.
Project description:We identified the mRNA and long non-coding RNA expression profiles of 100-day fetal skin between the dark and normal (white) skin in two breeds of goats using the deep RNA sequencing method. Case-control. Briefly, the 100-day fetal skin sampled from the normal and hyperpigmentated goats for deep sequencing, in triplicate for each breed, using Illumina
Project description:Rb null embryos exhibit defective fetal liver erythropoiesis. We used microarrays to compare Wt and Rb null fetal livers and to analyse gene expression differences which accompany and may underlie Rb null fetal liver degeneration, erythroid failure, and erythropoietic island dissolution. We used microarrays to compare Wt and Rb null fetal livers and analyse gene expression changes which accompany and may underlie fetal liver. Keywords: retinoblastoma, fetal liver, erythroblast, macrophage, cell death
Project description:We identified the mRNA and long non-coding RNA expression profiles of 100-day fetal skin between the dark and normal (white) skin in two breeds of goats using the deep RNA sequencing method.
Project description:mRNA expression differences between the liver and kidney of an adult male (homo sapien) were investigated using three technical replicates. The purpose of the experiment was to compare array data generated using Affymetrix with measures of expression obtained using RNAseq (a sequencing approach for measuring expression that utilizes Solexa technology). Keywords: kidney, liver
Project description:Purpose: The 10x Genomics Visium platform allows us to define the spatial topography of gene expression and provides detailed molecular maps that overcome limitations associated with sn/scRNA-seq and microscopy-based spatial transcriptomics methods. The goals of this study are to compare and identify unique transcriptome profiling (RNA-seq) signature between unfavorable and favorable Wilms Tumors and against human fetal kidney. Methods: Human fetal kidney and Wilms tumor spatial topography of gene expression were generated using the 10X Visium platform Results: Using an optimized data analysis workflow, we mapped the reads to the hg38 genome build and grouped the spots into 9 clusters based on gene expression profiles. Conclusion: Our study represents the first implement of Visium technology in human fetal kidney and Wilms Tumor tissue, providing a number of important functional insights about the spatial and molecular definitions of cell populations across human fetal kidney and different subtypes of Wilms Tumor through analyzing gene expression within the intact spatial organization of the human samples.