ABSTRACT
Summary: BioPyramid is a Python package, which serves as a scaffold for building an online application for the exploration of gene expression data. It is designed for bioinformaticians wishing to quickly share transformed data and interactive analyses with collaborators. Current R-based tools similarly address the need to quickly share 'omics'-data in an exploratory format, but these are generally small-scale, single-dataset solutions. Biopyramid is written in Python pyramid framework and scalable to address longer-term or more complex projects. It contains a number of components designed to reduce the time and effort in building such an application from scratch, including gene annotation, dataset models and visualization tools. Availability and implementation: Freely available at http://github.com/jarny/biopyramid. Implemented in python and javascript.
Subject(s)
Genomics , Software , Gene Expression , Internet , Molecular Sequence Annotation , Proteins/geneticsABSTRACT
Hematopoiesis is a multistage process involving the differentiation of stem and progenitor cells into distinct mature cell lineages. Here we present Haemopedia, an atlas of murine gene-expression data containing 54 hematopoietic cell types, covering all the mature lineages in hematopoiesis. We include rare cell populations such as eosinophils, mast cells, basophils, and megakaryocytes, and a broad collection of progenitor and stem cells. We show that lineage branching and maturation during hematopoiesis can be reconstructed using the expression patterns of small sets of genes. We also have identified genes with enriched expression in each of the mature blood cell lineages, many of which show conserved lineage-enriched expression in human hematopoiesis. We have created an online web portal called Haemosphere to make analyses of Haemopedia and other blood cell transcriptional datasets easier. This resource provides simple tools to interrogate gene-expression-based relationships between hematopoietic cell types and genes of interest.
Subject(s)
Blood Cells/cytology , Blood Cells/metabolism , Computational Biology , Gene Expression Regulation, Developmental , Hematopoiesis/genetics , Animals , Cell Differentiation/genetics , Cell Lineage/genetics , Cluster Analysis , Computational Biology/methods , Gene Expression Profiling , Humans , Mice , Web BrowserABSTRACT
Genome-scale technologies are increasingly adopted by the stem cell research community, because of the potential to uncover the molecular events most informative about a stem cell state. These technologies also present enormous challenges around the sharing and visualisation of data derived from different laboratories or under different experimental conditions. Stemformatics is an easy to use, publicly accessible portal that hosts a large collection of exemplar stem cell data. It provides fast visualisation of gene expression across a range of mouse and human datasets, with transparent links back to the original studies. One difficulty in the analysis of stem cell signatures is the paucity of public pathways/gene lists relevant to stem cell or developmental biology. Stemformatics provides a simple mechanism to create, share and analyse gene sets, providing a repository of community-annotated stem cell gene lists that are informative about pathways, lineage commitment, and common technical artefacts. Stemformatics can be accessed at stemformatics.org.
