1. ChipViewer is coded to visualize and analyze the tiling chip data.
ChipViewer Software
ChipViewer is coded to visualize and analyze the tiling chip data.
Data visualization
Data normalization
Data mining
Novel gene detection and fetching
Expression analyses

2. 1. ChipViewer:
ABSTRACT
The SSP tiling chips, which cover the whole Arabidopsis thaliana genomic sequences, are customarily designed for multi-purposes: To map transcriptional units of the Arabidopsis ORFeome, to mine and identify novel transcripts and small RNA species, to do high-throughput polymorphism detection among Arabidopsis accessions and to identify evolutionarily conserved non-coding regions in Brassica.
The ChipViewer, a Unix/Linux based application, is coded in-house in the Salk Institute Genomic Analysis Laboratory (SIGnAL) to qualitatively and quantitatively analyze the huge amount of data generated bye tiling chip experiments. Its X/Motif graphic user interface (GUI) allows uses to view chip expression profiles, de-convoluted chip expression profiles and histograms. An improved Match-only Integral Distribution algorithm (MOID) is introduced to call gene or genomic region absolute expression. In addition, a Relative Weight (RW), instead of normalization, is adopted to make it possible for universal comparison and analysis among different chip experiments. Furthermore, its comparative analysis tool allows for discovery of Single Feature Polymorphisms (SFPs) among Arabidopsis accessions, which will be useful markers for mapping QTLs using natural variations in the weed.
A snapshot can be reached at

3. 2. ChipViewer: Strategy of Chip Array Design (Test version)

4. 3. ChipViewer: De-Convolution of The Virtual Tiling Chip
In the tiling chip, probes are randomly allocated.
Raw
De-convoluted

5. 4. ChipViewer: Zoom in the virtual chip

6. 5. ChipViewer: Histograms of Hybridization Signals in Genomic Orders
Find: to find an annotated gene
Mining: to detect expressing regions
Specially novel regions
Fetch: to fetch a regional sequence

7. 6. ChipViewer: Histogram: hybridization and gene annotation

8. 7. ChipViewer: Normalization – Linear regression normalization
y = a x + b
After normalization: a = 1 and b = 0 for two sets of chip data
y = a x + b a b
y – log (intensity of the chip to be normalized)
x – log (intensity of the standard chip)
a – slope
b – intercept

9. 8. ChipViewer: Normalization – Linear regression normalization 2
Two sets of data different to each other

10. 9. ChipViewer: Normalization – Distribution normalization
Use a standard distribution or other chip’s distribution model to normalize a set of data
Normalization based on the distribution of the 2nd chip

11. 10. ChipViewer: Normalization – Comparing the 2 models
Linear regression model
Distribution based model

12. 11. ChipViewer: Statistic Methods and Algorithms
Weight – Statistical analyses
Cramer von Mises test ( two tails)
Kolmogorov-Smirnov test ( two tails)
Weight (one tail) n
Wt = Σ (SN(ƒ(i)) – F(ƒ(i))) d(ƒ(i))
Rw = Wt / Wo 1

13. 12. ChipViewer: Weight – Statistical analyses 2
NULL distribution
Chip distribution Di
DKS
Distribution of Selected probes Wt x

14. 13. ChipViewer: Relative Weight – Statistical analyses 3
NULL distribution
Chip distribution Di
Dks (i) Wt Wo
DKS (NULL)
Distribution of Selected probes
Rw = Wt / Wo x

15. 14. ChipViewer: Weight – Statistical analyses 4
DKS
Samples
NULL distribution  chip distribution
v p(v)

16. 15. ChipViewer: Weight – Statistical analyses 4-2
Samples
chip
NULL distribution  chip distribution

17. 16. ChipViewer: Detection of novel genes
Use Mining button to detect the expression regions.
This gene is now annotated as At1g09645 in the latest AGI genome.
Use Mining button to detect the expression regions.

18. 17. ChipViewer: Detection of novel genes 2
From the latest AGI genome to the future annotation
ATG
ATG
TAA
RAFL
Nothing in the latest AGI genome, but a new gene At1g11765 will be there in the future version.

19. 18. ChipViewer: Mapping of transcriptional units of ORFeome
From 2000v At1g09750 (MIPS) to the latest AGI At1g09750
2000 v Annotation (MIPS)
The latest AGI Annotation

20. 19. ChipViewer: Mapping of transcriptional units of ORFeome

21. 20. ChipViewer: Mapping of transcriptional units of ORFeome
Schematic of the Identification of New Genes
gDNA
mRNA
S (Salk) clones
C (Chip) clones

22. 21. ChipViewer: Identification of sm RNAs
5’GACCCAATAAGCCGCTCCGATTGGA 3’
CCB5

23. 22. ChipViewer: Evidence for Genes with Expression12 3 1 6 2
Putative exons in intergenic regions
330
431
1269 83
100
321
Chr. 2 Mb
chip 2d 96
117
328 Mb
chip 2c 79
104
300
Chr. 1 Mb
chip 1b 72
110
320 Mb
chip 1a
ORFs w/ evidence for expression
ORFs w/o cDNAs or ESTs
Total predicted ORFs
Regions covered
Tiling Arrays

24. 23. ChipViewer: Sense and anti-sense
Discovery of Sense and anti-sense signals in Plasmodium and Arabidopsis.
Sense
Anti-Sense
Signals of the gene PFC0110w in Plasmodium.

25. 24. ChipViewer: Data fetching
Detect
Fetch
Six frames
Sequence

26. 25. ChipViewer: Comparing multiple sets of data
There are 3 sets of the Plasmodium tiling chip data respectively in red, blue and green bars.
---- The Plasmodium tiling chip is a perfect match only chip

27. 26. ChipViewer: Comparing multiple sets of data (cluster tracks)
There are 9 sets of the chip data .

28. 27. ChipViewer: Outputs
Output of de-convoluted data ( raw/normalized)
Output of expression proportion – output of the signal proportion of exon, intron and intragenic regions.
Output of expression data mining – output of the expressing regions and their weights.
Output of all or selected probe sets and genes’ expressing data (statistical weight).

29. Acknowlegements
Thanks to Dr. Ecker, Dr. Lim and others at the Salk Institute Genomic Analysis Laboratory for their suggestions, comments and supports, as well as thanks to Dr. Winzeler and Dr. Grunenfielder from Scripps Institute.
Huaming Chen