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• Functional Genomics I Microarray Analysis

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The c-Src Protein
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Amino Acids
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Amino Acid Symbols
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Amino Acid Sequence of c-Src

• MGSNKSKPKDASQRRRSLEPAENVHGAGGGAFPASQTPSKPASADGHRGP
  SAAFAPAAAE
• PKLFGGFNSSDTVTSPQRAGPLAGGVTTFVALYDYESRTETDLSFKKGER
  LQIVNNTEGD
• WWLAHSLSTGQTGYIPSNYVAPSDSIQAEEWYFGKITRRESERLLLNAEN
  PRGTFLVRES
• ETTKGAYCLSVSDFDNAKGLNVKHYKIRKLDSGGFYITSRTQFNSLQQLV
  AYYSKHADGL
• CHRLTTVCPTSKPQTQGLAKDAWEIPRESLRLEVKLGQGCFGEVWMGTWN
  GTTRVAIKTL
• KPGTMSPEAFLQEAQVMKKLRHEKLVQLYAVVSEEPIYIVTEYMSKGSLL
  DFLKGETGKY
• LRLPQLVDMAAQIASGMAYVERMNYVHRDLRAANILVGENLVCKVADFGL
  ARLIEDNEYT
• ARQGAKFPIKWTAPEAALYGRFTIKSDVWSFGILLTELTTKGRVPYPGMV
  NREVLDQVER
• GYRMPCPPECPESLHDLMCQCWRKEPEERPTFEYLQAFLEDYFTSTEPQY
  QPGENL

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Information Transfer at the Sequence Level How a
Protein is Made

• DNA -gt RNA -gt Protein

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DNA
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Double-Stranded DNA
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Base Pairing in DNA
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Double Helical Structure of DNA
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RNA Ribonucleic Acid

• Differs from DNA
• 1. Sugar has an extra oxygen
• 2. Uracil (U) instead of thymine (T)
• 3. Single strand not double helix

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Protein Synthesis
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How Many Nucleotides Are Required to Code for an
Amino Acid?
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3 Nucleotides Code for an Amino Acid
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The Genetic Code
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DNA Sequence of Src

• CATCGAGGTTTTGAGAGGCTAACTCTCCCAAAAAGGACCATGGGTAGCAA
  CAAGAGCAAG
• CCCAAGGATGCCAGCCAGCGGCGCCGCAGCCTGGAGCCCGCCGAGAACGT
  GCACGGCGCT
• GGCGGGGGCGCTTTCCCCGCCTCGCAGACCCCCAGCAAGCCAGCCTCGGC
  CGACGGCCAC
• CGCGGCCCCAGCGCGGCCTTCGCCCCCGCGGCCGCCGAGCCCAAGCTGTT
  CGGAGGCTTC
• AACTCCTCGGACACCGTCACCTCCCCGCAGAGGGCGGGCCCGCTGGCCGG
  TGGAGTGACC
• ACCTTTGTGGCCCTCTATGACTATGAGTCTAGGACGGAGACAGACCTGTC
  CTTCAAGAAA
• GGCGAGCGGCTCCAGATTGTCAACAACACAGAGGGAGACTGGTGGCTGGC
  CCACTCGCTC
• AGCACAGGACAGACAGGCTACATCCCCAGCAACTACGTGGCGCCCTCCGA
  CTCCATCCAG
• GCTGAGGAGTGGTATTTTGGCAAGATCACCAGACGGGAGTCAGAGCGGTT
  ACTGCTCAAT
• GCAGAGAACCCGAGAGGGACCTTCCTCGTGCGAGAAAGTGAGACCACGAA
  AGGTGCCTAC
• TGCCTCTCAGTGTCTGACTTCGACAACGCCAAGGGCCTCAACGTGAAGCA
  CTACAAGATC
• CGCAAGCTGGACAGCGGCGGCTTCTACATCACCTCCCGCACCCAGTTCAA
  CAGCCTGCAG
• CAGCTGGTGGCCTACTACTCCAAACACGCCGATGGCCTGTGCCACCGCCT
  CACCACCGTG
• TGCCCCACGTCCAAGCCGCAGACTCAGGGCCTGGCCAAGGATGCCTGGGA
  GATCCCTCGG

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Translation of Src Gene to Src Protein

• CATCGAGGTTTTGAGAGGCTAACTCTCCCAAAAAGGACCATGGGTAGCAA
  CAAGAGCAAG
• M G S N
  K S K
• CCCAAGGATGCCAGCCAGCGGCGCCGCAGCCTGGAGCCCGCCGAGAACGT
  GCACGGCGCT
• P K D A S Q R R R S L E P A E N V
  H G A
• .
• .
• .
• GAGCGGCCCACCTTCGAGTACCTGCAGGCCTTCCTGGAGGACTACTTCAC
  GTCCACCGAG
• E R P T F E Y L Q A F L E D Y F T
  S T E
• CCCCAGTACCAGCCCGGGGAGAACCTCTAGGCACAGGCGGGCCCAGACCG
  GCTTCTCGGC
• P Q Y Q P G E N L

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Transcription of DNA and translation of RNA vary
with biological conditions
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2 kinds of microarray platforms

• Spotted Array - 2 color - Pat Brown (Stanford)
• Synthesized Oligonucleotide - 1 color -
  Affymetrix

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Spotted (2 Color) Arrays
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Concentrations from 2 Color Experiments
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Affymetrix 1 Color Arrays
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Spotted vs Affymetrix

• Spotted Arrays
• Advantages Long pieces.
• Disadvantages Uncertainties in spot reading.
• Affymetrix Arrays
• Advantages Probes in same place, can be read
  precisely.
• Disadvantages Short pieces.

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Concentrations from 1 Color Experiments
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Probeset intensity as an average of probe
intensities
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Problems with averaging probes

1. Var(probes within probeset) gt Var(The same
   probe across slides)
2. MMgtPM (40 of slides)

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Problems to be solved in chip reading

• 1. Highly variable probe intensities compared to
  probes set intensity.
• 2. Correct for nonspecific binding realistically.
  
• 3. Correct for background within chips.
• 4. Correct for intensity variation between chips.

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Steps in GCRMA

• 1. Background correction- in each chip.
• 2. Normalization - between chips.
• 3. Summarization of probes to probe sets.

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GCRMA Background Correction
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Boxplot of Unnormalized Chips
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Quantile Normalization
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Intensity Plots
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Contributions to probe intensity
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Constraint on probe-effects
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Median polish algorithm
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Expression ratios
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Need for a measure of variability
Experiment Replicate A Replicate B Average
1 2 6 4
2 1 15 8
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Approximation of the normal distribution
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Equation of the normal distribution
m
mean(average)
standard deviation
s
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Effect of the standard deviation
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Standard deviation and percent
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Estimates of the mean and standard deviation
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The z distribution
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Does experimental CO210.00mg/m3
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The t-distribution
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The t-distribution of the difference of 2 means
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Problems applying t-test to microarrays

• 1. Multiple tests - thousands of genes.
• 2. Multiple conditions- more than 2 conditions.
• Solution LIMMA
• LInear Models for Microarray Analysis.

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The log transformation of intensities
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The t-distribution of the difference of 2 means
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Variance Stabilization
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Benjamini-Hochberg False Discovery Correction

• Uncorrected p-value rate of false discovery if
  only 1 test.
• Corrected p-value rate of false discovery if all
  of the genes above it were tested and accepted.

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Components of Multiple Comparisons

• 1. The number of conditions.
• 2. The number of comparisons between conditions.

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Multiple Conditions
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Comparing 2 conditions out of 3
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Bonferroni Correction for Multiple Comparisons
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Bayesian Log Odds B-value
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AffylmGUI

• R (Statistical Programming Language)

Bioconductor (R Programs for Biology)
LIMMA
AffylmGUI 1 Color
Limma GUI 2 Color