A collection of annotated and harmonized human breast cancer transcriptome datasets, including immunologic classification.
Jessica P RoelandsJulie V DecockSabri BoughorbelDarawan RinchaiCristina MaccalliMichele CeccarelliMichael BlackCris PrintJeff ChouScott PresnellCharlie QuinnPuthen JitheshNajeeb SyedSalha B J Al BaderShahinaz BedriEna WangFrancesco M MarincolaDamien ChaussabelPeter KuppenLance D MillerDavide BedognettiWouter R L HendrickxPublished in: F1000Research (2017)
The increased application of high-throughput approaches in translational research has expanded the number of publicly available data repositories. Gathering additional valuable information contained in the datasets represents a crucial opportunity in the biomedical field. To facilitate and stimulate utilization of these datasets, we have recently developed an interactive data browsing and visualization web application, the Gene Expression Browser (GXB). In this note, we describe a curated compendium of 13 public datasets on human breast cancer, representing a total of 2142 transcriptome profiles. We classified the samples according to different immune based classification systems and integrated this information into the datasets. Annotated and harmonized datasets were uploaded to GXB. Study samples were categorized in different groups based on their immunologic tumor response profiles, intrinsic molecular subtypes and multiple clinical parameters. Ranked gene lists were generated based on relevant group comparisons. In this data note, we demonstrate the utility of GXB to evaluate the expression of a gene of interest, find differential gene expression between groups and investigate potential associations between variables with a specific focus on immunologic classification in breast cancer. This interactive resource is publicly available online at: http://breastcancer.gxbsidra.org/dm3/geneBrowser/list.
Keyphrases
- gene expression
- rna seq
- single cell
- genome wide
- machine learning
- high throughput
- deep learning
- endothelial cells
- dna methylation
- electronic health record
- big data
- health information
- healthcare
- emergency department
- pluripotent stem cells
- social media
- metabolic syndrome
- artificial intelligence
- risk assessment
- skeletal muscle
- single molecule
- data analysis
- human health
- glycemic control
- weight loss
- genome wide analysis