Ns126:Calendar/NOTES/2015-7-12: Difference between revisions
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File:WGBS. | File:WGBS.Hclust.Complete.phase2.jpeg|Figure 1A. Hierarchical clustering based on WGBS revealed the relationships between hESC, N37 normals, Salk normals and cancers | ||
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*consider: batch differences in read depth, read length or other artifacts. | *consider: batch differences in read depth, read length or other artifacts. |
Revision as of 06:49, 21 July 2015
Materials and Method
Dr. Zhang update the MONOD methylation haplotype result and therefore I can check the latest result in the relationship between samples and check the distinguish ability of cancer and normals based on methylation haplotype load.
About the data processing, check: http://genome-tech.ucsd.edu/LabNotes/index.php/Kun:LabNotes/MONOD/2015-7-6
Result
Relationship between samples in the propestive of hierarchical clustering based on MHL
N37<-c("Colon","Frontal lobe","Heart","Small intestine","Liver","Lung","Skeletal muscle","Pancrease","Stomach") N37<-c("LymphNodes","Blood","Colon","BrainCRBM","Heart","Liver","Lung","Muscle","Pancreas","Stomach") # modified
- WGBS.Hclust.Complete.phase2.jpeg
Figure 1A. Hierarchical clustering based on WGBS revealed the relationships between hESC, N37 normals, Salk normals and cancers
- consider: batch differences in read depth, read length or other artifacts.
- RRBS.PhaseI.Cluster.Revise.jpeg
Figure 1B. Hierarchical clustering based on RRBS revealed the relationships between Plasma, Nomal and Cancer tissues.
- SeqCap.Phase2.Cluster.Revised.jpeg
Figure 1C.Hierarchical clustering based on SeqCap revealed the relationships between Plasma, Nomal and Cancer tissues.