Ns126:Calendar/NOTES/2015-7-12: Difference between revisions
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==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== | ==Result== | ||
<gallery widths=400px heights= | ===MHL Distrbution in 3 dataaset=== | ||
File:WGBS. | |||
<gallery widths=800px heights=400px> | |||
File:WGBS.Boxplot.phase2.withcancer.jpeg|Figure 1A-1. Boxplot for the distribution of MHL in WGBS dataset(total) | |||
File:WGBS.Boxplot.phase2.jpg.jpeg|Figure 1A-2. Boxplot for the distribution of MHL in WGBS dataset(part) | |||
</gallery> | |||
<gallery widths=400px heights=400px> | |||
File:RRBS.Boxplot.pahse2.jpeg|Figure 1C. Boxplot for the distribution of MHL in RRBS dataset | |||
File:SeqCap.phase2.boxplot.jpeg|Figure 1D. Boxplot for the distribution of MHL in SeqCap dataset | |||
</gallery> | |||
===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 | |||
<gallery widths=800px heights=400px> | |||
File:WGBS.Hclust.Complete.phase2.jpeg|Figure 1A. Hierarchical clustering based on WGBS revealed the relationships between hESC, N37 normals, Salk normals and cancers | |||
</gallery> | |||
*consider: batch differences in read depth, read length or other artifacts. | |||
<gallery widths=800px heights=400px> | |||
File:RRBS.PhaseI.Cluster.Revise.jpeg|Figure 1B. Hierarchical clustering based on RRBS revealed the relationships between Plasma, Nomal and Cancer tissues. | |||
</gallery> | |||
<gallery widths=800px heights=400px> | |||
File:SeqCap.Phase2.Cluster.Revised.jpeg|Figure 1C.Hierarchical clustering based on SeqCap revealed the relationships between Plasma, Nomal and Cancer tissues. | |||
</gallery> | </gallery> | ||
[[File: | |||
[[File: | ===Relationship between samples in the propestive of PCA analysis based on MHL=== | ||
[[File:WGBS.MONOD.PCA.2.jpeg]] | |||
==== Functional enrichment of the loci that have the highest loading to PC1 and PC2==== | |||
==== Methylation 450K sample with CD, ESC and Cancer sample in the sapce of PC1 and PC2==== | |||
===Relationship between MHL and Methylation entropy=== | |||
====Definition==== | |||
[[File:Methylation.Entropy.jpg]] |
Latest revision as of 07:41, 21 July 2015
Materials and Method[edit]
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[edit]
MHL Distrbution in 3 dataaset[edit]
- WGBS.Boxplot.phase2.withcancer.jpeg
Figure 1A-1. Boxplot for the distribution of MHL in WGBS dataset(total)
- WGBS.Boxplot.phase2.jpg.jpeg
Figure 1A-2. Boxplot for the distribution of MHL in WGBS dataset(part)
- RRBS.Boxplot.pahse2.jpeg
Figure 1C. Boxplot for the distribution of MHL in RRBS dataset
- SeqCap.phase2.boxplot.jpeg
Figure 1D. Boxplot for the distribution of MHL in SeqCap dataset
Relationship between samples in the propestive of hierarchical clustering based on MHL[edit]
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.