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Pancreatic β and α cells play essential roles in maintaining glucose homeostasis. However, the mechanisms by which these distinct cell populations are generated, expand, and mature during pancreas development remain unclear. In this study, we addressed this critical question by performing a single-cell transcriptomic analysis of mouse β and α cells sorted from fetal to adult stages. We discovered that β and α cells use different regulatory strategies for their maturation and that cell proliferation peaks at different developmental times. However, the quiescent and proliferative cells in both the β lineage and α lineage are synchronous in their maturation states. The heterogeneity of juvenile β cells reflects distinct cell-cycling phases, origins, and maturation states, whereas adult β cells are relatively homogeneous at the transcriptomic level. These analyses provide not only a high-resolution roadmap for islet lineage development but also insights into the mechanisms of cellular heterogeneity, cell number expansion, and maturation of both β and α cells.
Pubmed ID: 28467935 RIS Download
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Software package for differential gene expression analysis based on the negative binomial distribution. Used for analyzing RNA-seq data for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates.
View all literature mentionsThis unknown targets Rabbit IgG (H+L)
View all literature mentionsTHIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 30,2023. Software for differential gene expression analysis based on the negative binomial distribution. It estimates variance-mean dependence in count data from high-throughput sequencing assays and tests for differential expression.
View all literature mentionsGOstat is a tool that allows you to find statistically overrepresented Gene Ontologies within a group of genes. The Gene-Ontology database (GO: http://www.geneontology.org) provides a useful tool to annotate and analyze the function of large numbers of genes. Modern experimental techniques, as e.g. DNA microarrays, often result in long lists of genes. To learn about the biology in this kind of data it is desirable to find functional annotation or Gene-Ontology groups which are highly represented in the data. This program (GOstat) should help in the analysis of such lists and will provide statistics about the GO terms contained in the data and sort the GO annotations giving the most representative GO terms first. Run GOstat: * Go to search form - Computes GO statistics of a list of genes selected from a microarray. * GOstat Display - You can store results from a previously run and view them here, either by uploading them as a file or putting them on a selected URL. * Upload Custom GO Annotations - This allows you to upload your own GO annotation database and use it with GOstat. Variants of GOstat: * Rank GOstat - Takes input from all genes on microarray instead of using a fixed cutoff and uses ranks using a Wilcoxon test or either ranks or pvalues to score GOs using Kolmogorov-Smirnov statistics. * Gene Abundance GOstats - Takes input from all genes on microarray and sums up the gene abundances for each GO to compute statistics. * Two list GOstat - Compares GO statistics in two independent lists of genes, not necessarily one of them being the complete list the other list is sampled from. Platform: Online tool
View all literature mentionsSoftware R package. Methods for Cluster analysis. Performs variety of types of cluster analysis and other types of processing on large microarray datasets.
View all literature mentionsSoftware tool for fast and high throughput alignment of shotgun cDNA sequencing reads generated by transcriptomics technologies. Fast splice junction mapper for RNA-Seq reads. Aligns RNA-Seq reads to mammalian-sized genomes using ultra high-throughput short read aligner Bowtie, and then analyzes mapping results to identify splice junctions between exons.TopHat2 is accurate alignment of transcriptomes in presence of insertions, deletions and gene fusions.
View all literature mentionsOpen source software package for statistical programming language R to create plots based on grammar of graphics. Used for data visualization to break up graphs into semantic components such as scales and layers.
View all literature mentionsSoftware R package for multivariate analysis which takes into account different types of data structure. Data can be organized in groups of variable, groups of individuals, or into hierarchy of variables.
View all literature mentionsTHIS RESOURCE IS NO LONGER IN SERVICE. Documented on February 28,2023. Software Python package that provides infrastructure to process data from high-throughput sequencing assays. While the main purpose of HTSeq is to allow you to write your own analysis scripts, customized to your needs, there are also a couple of stand-alone scripts for common tasks that can be used without any Python knowledge.
View all literature mentionsQuality control software that perform checks on raw sequence data coming from high throughput sequencing pipelines. This software also provides a modular set of analyses which can give a quick impression of the quality of the data prior to further analysis.
View all literature mentionsUser interface software for Carl Zeiss light microscopy imaging systems. ZEN is the universal user interface you will see on every imaging system from ZEISS. After selecting fluorophore, ZEN applies the necessary settings to collect and organize data.
View all literature mentionsMus musculus with name B6.Cg-Gt(ROSA)26Sortm14(CAG-tdTomato)Hze/J from IMSR.
View all literature mentionsTHIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 30,2023. Software for differential gene expression analysis based on the negative binomial distribution. It estimates variance-mean dependence in count data from high-throughput sequencing assays and tests for differential expression.
View all literature mentionsTHIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 30,2023. Software for differential gene expression analysis based on the negative binomial distribution. It estimates variance-mean dependence in count data from high-throughput sequencing assays and tests for differential expression.
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