BloodSpot: a database of gene expression profiles and transcriptional programs for healthy and malignant haematopoiesis.
Frederik Otzen BaggerDamir SasivarevicSina Hadi SohiLinea Gøricke LaursenSachin PundhirCasper Kaae SønderbyOle WintherNicolas RapinBo T PorsePublished in: Nucleic acids research (2015)
Research on human and murine haematopoiesis has resulted in a vast number of gene-expression data sets that can potentially answer questions regarding normal and aberrant blood formation. To researchers and clinicians with limited bioinformatics experience, these data have remained available, yet largely inaccessible. Current databases provide information about gene-expression but fail to answer key questions regarding co-regulation, genetic programs or effect on patient survival. To address these shortcomings, we present BloodSpot (www.bloodspot.eu), which includes and greatly extends our previously released database HemaExplorer, a database of gene expression profiles from FACS sorted healthy and malignant haematopoietic cells. A revised interactive interface simultaneously provides a plot of gene expression along with a Kaplan-Meier analysis and a hierarchical tree depicting the relationship between different cell types in the database. The database now includes 23 high-quality curated data sets relevant to normal and malignant blood formation and, in addition, we have assembled and built a unique integrated data set, BloodPool. Bloodpool contains more than 2000 samples assembled from six independent studies on acute myeloid leukemia. Furthermore, we have devised a robust sample integration procedure that allows for sensitive comparison of user-supplied patient samples in a well-defined haematopoietic cellular space.
Keyphrases
- gene expression
- electronic health record
- big data
- adverse drug
- dna methylation
- acute myeloid leukemia
- genome wide
- copy number
- endothelial cells
- case report
- induced apoptosis
- machine learning
- emergency department
- palliative care
- data analysis
- cell therapy
- single cell
- cell cycle arrest
- transcription factor
- pi k akt
- induced pluripotent stem cells