Genome visualization challenges
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The document discusses challenges and opportunities for visualizing genomic data. It explores areas like comparative genomics, gene expression, protein analysis, pathways, and systems modeling that could benefit from improved visualization. New approaches and technologies are needed to integrate diverse data types and enable exploration, analysis, and interpretation. Emerging techniques from information visualization, like semantic zooming and progressive disclosure, could help make genomic data more accessible and understandable. Platforms and standards like GA4GH aim to facilitate discovery and sharing of genomic data.
Genome visualization challenges
- 1. Addressing future challenges for visualising genomic data Alberto Labarga – Dec 2015 Addressing future challenges for visualising genomic data Alberto Labarga – Dec 2015
- 14. ?
- 15. Comparative genomics Comparative genomics Sequence (DNA/RNA) & phylogeny Sequence (DNA/RNA) & phylogeny Regulation of gene expression; transcription factors & micro RNAs Regulation of gene expression; transcription factors & micro RNAs Protein sequence analysis & evolution Protein sequence analysis & evolution Protein families, motifs and domains Protein families, motifs and domains Protein structure & function: computational crystallography Protein structure & function: computational crystallography Protein interactions & complexes: modelling and predictionProtein interactions & complexes: modelling and prediction Chemical biologyChemical biology Pathway analysisPathway analysis Systems modelling Systems modelling Image analysisImage analysis Data integration & literature miningData integration & literature mining
- 19. reimagine the genome browser?
- 24. A grammar of graphics
- 25. ggplot
- 26. D3.js
- 27. bioJS
- 28. pViz
- 30. Everything is a platform
- 32. Service that make it easy to find data from a range of secondary data sources, then consume the data in a usable and unified format. Several of these services are trying to create marketplaces for data, envisioning that data providers can offer their data sets for sale to data seekers
- 33. a place where we encourage... support... enable... our communities
- 39. Usability
- 40. Chr5: 133,876,119 – 134,876,119 Genes Transcription Mouse orthology TF binding Histone mods SNPs Repeats Density of biological information in the human genome
- 43. Which gene annotation to use?
- 44. Integrating different types of annotation data Promoter Proximal enhancer
- 45. progressive disclosure semantic zooming resolution dependent data smoothing attention routing
- 47. New layouts
- 58. New charts
- 59. Hive plot
- 60. Space maps
- 61. curve maps
- 62. GA4GH
- 64. Genome browser in a box
- 65. Docker, spark, avro, etc