Transcript Poster PKDD07 - University of California, Riverside

M. Vlachos, B. Taneri, E. Keogh, P.S. Yu
IBM Research, NY
Scripps Genome Center, San Diego
University of California, Riverside
how can we visualize DNA data?
I think
it’s time I
bought that
new pair of
reading
glasses…
GTTAATGTAGCTTAAATATTTATAAAGCAAAACACTGAAAATGTTTAGATGGGTTTAATTAACCCCATTGACATTAAAGGTTTGGTCC
CAGCCTTTCTATTAGTTCTAAACAGACTTACACATGCGAGCATCTACATCCCAGTGAGAACGCCCTCTAAATCATCAAGGATCAAA
AGGAGCGGGTATCAAGCACACTAACACTAGTAGCTCACAACGCCTCGCTTAGCCACACCCCCACGGGACACAGCAGTGATAAAA
ATTAAGCCATGAACGAAAGTTTGACTAAGTCATGTTTACAAGGGTTGGTAAACTTCGTGCCAGCCACCGCGGTCATACGATTAACC
CAAATTAATAGAAACACGGCGTAAAGAGTGTTAAGGAGTCACGTAAAATAAAGTCAAGCCTTAATTAAGCTGTAAAAAGCCCTAAT
TAAAACTAAGCCAAACTACGAAAGTGACTTTAATATAATCTGATTACACGACAGCTAAGACCCAAACTGGGATTAGATACCCCACT
ATGCTTAGCCATAAACTCTAATAGTCACAAAACAAGACTACTCGCCAGAGTACTACTAGCAATAGCCTAAAACTCAAAGGACTTGG
CGGTGCTTCATACCCCCCTAGAGGAGCCTGTTCTATAAACGATAAACCCCGATCAACCTCACCAACCCTTGCTACTCCAGTCTATA
TACCGCCATCTT………….
CAGCAAACCCTAAAAGGGAACGAAAGTAAGCATAACCATCCTACATAAAAACGTTAGGTCAAGGTGTAACCTATGGGTTGGGAAG
AAATGGGCTACATTTTCTATATTAAGAACATTCCTTATACTCACACGAAAGTTTTTATGAAACTTAAAAACCAAAGGAGGATTTAGTA
GTAAATCAAGAGCAGAGTGCTTGATTGAACAAGGCCATGGAGCACGCACACACCGCCCGTCACCCTCCTCAAGTACCCTAGCAA
AGCCCCAGTTCGTTAACTCACGCCAAGCAATCATACGAGAGGAGACAAGTCGTAACAAGGTAAGCATACCGGAAGGTGTGCTTG
GATGAATCAAGATATAGCTTAAACAAAGCATCTAGTTTACACCTAGAAGATTCCACACCCTGTGTATATCTTGAACCAATTCTAGCC
CACACCCTCCCCACTTCTACTACTACAAACCAATCAAATAAAACATTCACCATACATTTTAAAGTATAGGAGATAGAAATTTAATTAC
CAGTGGCGCTATAGAGATAGTACCGTAAGGGAAAGATGAAAGAAAACCTAAAAGTAGTAAAAAGCAAAGCTTACCCCTTGTACCT
TTTGCATAATGACTTAACTAGTAATAACTTAGCAAAGAGACCTTAAGTTAAATTACCCGAAACCAGACGAGCTACTTATGAGCAGTA
TTTAGAACGAAC…………...
Thousands or millions of basepairs long
• Humans cannot easily compare or visualize text
• We understand and visualize better shapes
• Can we find a way to visually represent bulks of DNA
sequences?
• How can we represent the relationships between DNA
sequences in an accessible manner?
dendrogram visualization
• Dendrograms present a
hierarchy of affinity/similarity
• They still do not provide
any solutions for the DNA
representation
GATAAAAATTAAGCCATG
AACGAAAGTTTGACTAA
GTCATGTTTACAAGGGTT
GGTAAACTTCGTGCCAG
CCACCGCGGTCATACGA
TTAACCCAAATTAATAGA
AACACGGCGTAAAGAGT
GTTAAGGAGTCACGTAA
AATAAAGTCAAGCCTTAA
TTAAGCTGTAAAAAGCC
CTAATTAAAACTAAGCCA
AACTACGAAAGTGACTTT
AATATAATCTGATTACA
GATAAAAATTAAGCCATG
AACGAAAGTTTGACTAAG
TCATGTTTACAAGGGTTG
GTAAACTTCGTGCCAGC
CACCGCGGTCATACGAT
TAACCCAAATTAATAGAA
ACACGGCGTAAAGATAA
GGAGTCACGTAAAATAA
AGTCAAGCCTTAATTAAG
CTGTAAAAAGCCCTAATT
AAAACTAAGCCAAACTAC
GAAAGTGACTTTAATATA
ATCTGATTACA
AATTGATAAAAATTAAGC
CATGAACGAAAGTTTGA
CTAAGTCATGTTTACAAG
GGTTCGTGCCAGCCACC
GCGGTCATACGATTAAC
CCAAATAGAAACACGGC
GTAAAGATAAGGAGTCA
CGTAAAATAAAGTCAAG
CCTTAATTAAGCTGTAAA
AAGCCCTAATTAAAACTA
AGCCAAACTACGAAAGT
GACTTTAATATAATCTGA
TTACATTGGTAAAC
• Dendrograms cannot
capture pairwise
relationships
- They are lost during the
grouping
Other techniques:
• HyperTree
• PattVision
what we propose …
• Transform sequences into 2dimensional trajectories
• Compute elastic matching
between DNA trajectories
• Plot their relationships on
the 2D plane using a
spanning-tree mapping
DNA string
…GTACTTAGCGATTTAAATTC…
Easier to
visualize
and compare
trajectories
rather than
strings
Trajectory
(and possible
simplification)
Spanning Tree
Visualization
+ Relative Distance
towards pivot point
B
A
D
W
F
R
H
I
L
R2
converting DNA to trajectories
• Given an initial point on the 2D space (e.g. [0,0])
• Start moving up/down/left/right based on the
DNA letter you encounter
• Similar DNA sequences will
result into similar trajectories
A
G
• This process will convert a
long string of nuclotides into
a 2D trajectory that can be
easily visualized
• Resulting trajectories can
be downsampled or
compressed for easier
plotting
T
C
Example:
Trajectory(i)= Trajectory(i-1) + V
…GAATTC…
Cow
DNA
DNA
Trajectory
example
Human vs Chimpanzee
• Species with similar DNA
content will also have very
similar DNA trajectories
• The elastic matching
offered by the warping
function can find flexible
similarities
Human vs Bear
Dynamic Time Warping
Primer
• Use dynamic programming
to solve the matching
problem
is this representation meaningful?
Eutheria
Cetartiodactyla
Hominidae
Balaenoptera
Carnivora
Ursus
Proboscidea
Panines
• The dendrogram on the pairwise distances between the trajectories is
correct
• It accurately captures the predominant views about affinity of species
spanning tree visualization
• The distance between any tree points can
be perfectly retained on the 2D space
• For additional points we can retain the
distance to the NN point + to one pivot point
• Out of N2 distances we can preserve a total
of:
3 + 2(n-3) distances
Advantages of the Mapping:
• Important distances are
exactly preserved
• Local and global structure is
preserved
• Preservation of distances
against the pivot point
allows for the very powerful
visualization
visualization: humans & ‘relatives’
Using warping
distance
• Pivot point is the human
• Species that diverged
closer in time, are also
placed closer on the 2D
space.
Using euclidean
distance
• Gibbon is erroneously placed
closer to human compared to the
orangutan.
visualization: relationship between mammals
Hippopotamus is indeed
closer to whale than
to any other species Cetartiodactyla
B. M. Ursing and U. Arnason. Analyses of
mitochondrial genomes strongly support a
hippopotamus-whale clade. In Proc. of the Royal
Society of London, Series B, vol 265: 2251-2255,
1998.
Human is closer to
pygmy chimpanzee
than to regular
chimpamzee.
C. Lockwood, W. Kimbel, and J. Lynch.
Morphometrics and hominoid phylogeny:
Support for a chimpanzee-human clade and
differentiation among great ape sub-species.
In Proc. Natl. Acad. Sci. USA, 101(13),
4356-4360, 2004.
spanning tree for non-metric distances
Enclosed Reference
Circles
• When dealing with nonmetric distance (like the
DTW) the circles in the
spanning-tree visualization
method may not intersect.
• So now we need to find the
point in 2D space that is
closer to the two center
circles.
Disjoint Reference
Circles
• The reference circles can
either enclose each other or
be one outside the other.
C is the point closer to
the centers A1 and A2
of the two reference
circles.
extensions (search and indexing)
• Can we utilize advanced
compression and indexing schemes
for the DNA trajectories in order to do
fast prefiltering between millions of
DNA sequences?
Project all sequences into a new space, and search
this space instead (eg project trajectory from 100-D
space to 2-D space)
Feature 1
A
B
C
Feature 2
query
Organize the low-dimensional points into a
hierarchical ‘index’ structure.
extensions (medical screening)
• DNA trajectories can be a
interesting approach to clinical
screening and diagnostics
• E.g. does this tissue/cell look more
like a cancerous one or not?
• By evaluating the distance inbetween the DNA trajectories, can
we evaluate the cancer stage of a
tissue?
Cancer Tissues
• Perform clustering
• Discover Classification Rules,
e.g. through Nearest Neighbors
X
Normal Tissues
Is this tissue
cancerous or not
and at what
stage?