Download Good Statistics Can Help You Discover Biological Process

Good Statistics Can Help You Discover Biological
Process Using Modern Genomic Assays
Tom Downey
President, Partek Inc.
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Who is Partek?

Founded in 1993

Based in St. Louis, MO USA

Focused on Genomics


Thousands of customers
worldwide
Building tools for both
biologists and bioinformaticians
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Partek® GS™ - Software for Integrated Genomics

Multi-Platform Support
• Multi-Assay Support
• Gene Expression
• Alternative Splicing
• miRNA
• Copy Number Variation
• ChIP-Chip, ChIP-Seq
• RNA-Seq
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Partek® GS™ for Integrated Genomics
Microarray
Genome
• Copy Number
• Total & Allele Specific
• Association
• Loss of Heterozygosity
&
Next Generation Sequencing
Regulation
Transcriptome
• Gene Expression
• Exon/Alternative Splicing
• DGE & mRNA –Seq
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• ChIP-Chip
• ChIP-Seq
• microRNA
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What is Statistics?
•
Statistics (Source: www.m-w.com)

a branch of mathematics dealing with
collection, analysis,
interpretation,and presentation of
masses of numerical data
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The Role of Experimental Design
•
•
The goal of statistics is to find signals in a sea of noise
The goal of experimental design is to reduce that noise
so true biological signals can be found with as small a
sample size as possible
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Example 1: ER+ Positive Breast Cancer
Study

Evaluate expression of ER+ breast
cancer cell lines



5 treatments
3 time points
2 replicates
Control
Estrogen E2 +
(E2)
ICI
E2 +
Raloxifene
E2 +
Tomoxifen
0 hr
2
0
0
0
0
8 hr
0
2
2
2
2
48 hr
0
2
2
2
2
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As Seen Using PCA
Samples
clustered by
batches “A”
and “B”
•
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As Seen Using Hierarchical Clustering
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Good News!
•
•
Since the treatments were perfectly balanced with the
batches, the batch can be can be completely removed from
the data.
With a simple 2-way ANOVA, this gene was #228 on the
gene list and would not pass multiple test correction for
significance. With a 3-way ANOVA including batch, it was #2
on the gene list.
Factor
2-way ANOVA
3-way ANOVA
Treatment
0.00391497
3.43275e-007
Time
0.396031
0.00964938
Treatment*Time
0.100862
3.56752e-005
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Balanced with respect to Batch

Monday
Control
Estrogen E2 +
(E2)
ICI
E2 +
Raloxifene
E2 +
Tomoxifen
8 hr
1
1
1
1
48 hr
1
1
1
1
Estrogen E2 +
(E2)
ICI
E2 +
Raloxifene
E2 +
Tomoxifen
8 hr
1
1
1
1
48 hr
1
1
1
1
0 hr

1
Tuesday
Control
0 hr
1
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#2 Most Significant Gene
MedianA=8.5
MedianB=9.7
Tue/Mon more
than 2-fold
Monday on top, Tuesday on bottom
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ER+ B.C. Unadjusted Signal
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ER+ B.C. Batch-Adjusted Signal
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Experiment Design: Consider Batch Effects
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How NOT to Ruin Your Next Experiment!
•
•
•
Samples are frequently “organized”
by treatment groups.
Samples are then processed in
batches corresponding to treatment
groups.
E.g. Control samples processed on
Monday, Treated samples processed
on Tuesday.
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Statistical Analysis
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A brief history of statistics
Pearson
1900-1901:
Regression,
Correlation
(r), ChiSquare
Student (William Gosset)
1908:
T-test
Fisher
1923:
ANOVA
1934: Statisticians began to realize that these
were all re-inventions of the “linear model”…
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Analysis of Variance


Analysis (m-w.com)
 separation of a whole into
its component parts
“Analysis of Variance”
(ANOVA) measures the
effect of multiple
experimental factors (or
phenotypes) on expression
levels.
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1.15%
Treatment
17.49%
Time
17.40%
58.36%
Treatment *
Noise
Batch
1.64%
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2-way ANOVA

Total variance is partitioned into variability due to
influencing factors and the rest is assumed to be due to
random error (noise).
18.64%
Treatment
17.40%
58.36%
Time
Treatment * Time
Noise
1.64%

R2=81% for 2-way ANOVA
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ANOVA Partitions Variability

Total variance is partitioned into variability due to
influencing factors and the rest is assumed to be due to
random error (noise).
1.15%
Treatment
17.49%
Time
17.40%
58.36%
Treatment * Time
Noise
Batch
1.64%

R2=99% when Batch included
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Monitor Biological Trends with GO Enrichment
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Upregulation/Downregulation by Biological Process
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Correlation is a form of ANOVA

Correlating a continuous variable with a binary
variable is mathematically equivalent to a ttest, or 1-way ANOVA
Gene A
Gene B
8.3
5.6
7.1
7.3
6.8
8.2
8.9
6.1
7.3
6.9
…
…
…
…
…
…
…
…
…
AML/ALL
0 (AML)
1 (ALL)
1 (ALL)
0 (AML)
1 (ALL)
…
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Example 2: Aging Study

Aging Study:


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

Examine how gene expression profiles change
with age (GEO GSE8479)
Total of 49 Adult Subjects
N=24 Young (Age 18-29)
N=25 Old (Age 65-84)
26 Female, 23 Male
~6 Beadchips (6*8=48)
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Simple Correlation of Age w/ Genes


R2=81% for correlation (1-factor ANOVA)
Noise = 19%
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Correlation of Age w/ Genes, considering
other effects


R2=90% using 3-factor ANOVA
Noise = 10%
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Partek ANOVA

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
Balanced & Unbalanced &
Incomplete
Random & Fixed Effects
(mixed model)
Numeric & Categorical
Variables
Nested/Nesting
(Hierarchical) designs
Any number of factors
Flexible Linear Contrasts
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Sample
preparation
High-Throughput
Sequencing
Alignment
Downstream
Analysis
Publication
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Partek Genome Browser – RNA-Seq Data
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Next Generation Sequencing Data Along with Exon
Microarray Data
Partek® Genomics Suite™




Powerful Statistics with Interactive Visualization
Fast, Memory-efficient
Easy to Use
Support for a Wide Variety of Genomic Technologies
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
3’ Gene Expression
Whole Transcript Exon & Gene
Copy Number, AsCN, LOH
microRNA Expression
CHIP-chip
CHIP-Seq and RNA-Seq
Taqman Real-time PCR
Genomic Integration
Integrated with Public Genomic Resources: NCBI GEO, UCSC, Ensembl,
Gene ontology, KEGG etc.
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Micro RNA - hsa_miR_25
miRNA negatively correlated with its mRNA
target
mRNA expression - 208860_s_at
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