Other genomic arrays: Methylation, chIP on chip… UBio Training Courses.
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Transcript of Other genomic arrays: Methylation, chIP on chip… UBio Training Courses.
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Other genomic Other genomic arrays: Methylation, arrays: Methylation,
chIP on chipchIP on chip……UUBBioio Training Courses Training Courses
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SNP-arrays and copy SNP-arrays and copy numbernumber
Genotyping arrays can detect CNVsGenotyping arrays can detect CNVs
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Copy numbers from SNP arrays
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Illumina SNP arrays: Hybridization to Universal IllumiCodeTM
Inte
nsity
<->
Cop
y nu
mbe
r
Illumina uses the same technology for methylation arrays(bi-sulfited nucleotides are like SNPs)
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Calculation of aCGH-like ratios
Median R CEPH Individual R cell line(NCI60)
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Methylation arraysMethylation arrays
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BeadArrays
o Until 12 samples per chip.o 27,578 CpG loci, >14.000 genes o 2 beads per locus (methylated/no methylated)o Random distribution (50 mer)o Input: Bisulphyted DNA o Includes probes for the promoter regions of miRNA 110 genes
METHYLATION MICROARRAYSIn
fin
ium
Hu
man
Meth
yla
tion
27
Bead
Ch
ip
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Illumina Golden Gate Assay
• Until 147,456 DNA methylation measures simultaneously.
• Resolution: 1 CpG
•Until 96 samples simultaneously
• GoldenGate Methylation Cancer Panel I 1,505 CpG loci selected from 807
gene
• Allows custom designs
METHYLATION MICROARRAYS
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SOFTWARE
Lumi package (Import, background correction, normalization)Beadarray package (Import, QC)Methylumi (Import, QC ,normalization, differential meth.)
Bead Studio Genome StudioMethylation modulehttp://www.illumina.com/pages.ilmn?ID=196
METHYLATION MICROARRAYS
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DIFFERENTIAL METHYLATION
METHYLATION MICROARRAYS
Bead Studio Genome StudioMethylation modulehttp://www.illumina.com/pages.ilmn?ID=196
Beta values:
β= Imethylated/Imethylated+Ino_methylated
β1 0
Hypermethylated Hypomethylated
0.7 0.3
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NORMALIZATION
METHYLATION MICROARRAYS
Methylumi normalization
1) Calculate medians for Cy3 and Cy5 at high an low betas2) Cy5 medians adjusted to Cy3 channel (dye bias)3) Recalculate betas with new intensities
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DIFFERENTIAL METHYLATION
METHYLATION MICROARRAYS
Wilcoxon rank-test (UBio)Limma (Pomelo)Permutations (Pomelo)
βs
FDR<0.05 Median βs class AMedian βs class B
+
Differentially methylated genes
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ChIP on chipChIP on chip
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ChIP on Chip
We thank Chris Glass lab, UCSD, for the original slide
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Discover protein/DNA interactions!!
ChIP on Chip
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ChIP on Chip software
Chip Analytics
WORKFLOW I.
1. Pre-normalization.Background substraction: Foreground – backgroundDefault: Median blank substraction Each channel – median negative controls
2. Normalization (dye-byas and interarray normalization) Default : Median dye-byas, median interarray. Recommended: Loess
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ChIP on Chip softwareChip Analytics
WORKFLOW II.
3. Error modelling To identify which probes are most representative of binding events: P(X)=P-value of a single probe matching event P(Xneighb)= Positive signals in a probe should be corroborated by the signals of probes that are its genomic neighbors,
provided they are close enough P(Xneighb) follows a Gaussian distribution Both the P(X) and the P(Xneighb) values of a probe need to satisfy significance thresholds in order for a probe to be considered as representing a binding event
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ChIP on Chip softwareChip Analytics
WORKFLOW III.4. Segment identification (clusters of enriched probes)
5. Gene identification-Segment, Gene or Probe report (Gene or probe ID, Chr, Start, End, p(X)…)
bp
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CoCashttp://www.ciml.univ-mrs.fr/software/cocas/index.html
Agilent platform
NormalizationQC ReportGenome VisualizationPeak Finder
Benoukraf et al. Bioinformatics 2009.
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UBio training courses: See “Course on Introduction to Sequence Analysis”
Weeder: Motif discovery in sequences from co-regulated genes (single specie).
WeederH: Motif discovery in sequences from homologous genes.
Pscan: Motif discovery in sequences from co-regulated genes (JASPAR,TRANSFAC matrices)
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