Guided visual exploration of patient stratifications in cancer genomics

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Talk presented at the "Beyond the Genome 2014: Cancer Genomics" conference (10 October 2014) http://www.beyond-the-genome.com/2014/ Cancer is a heterogeneous disease, and molecular profiling of tumors from large cohorts has enabled characterization of new tumor subtypes. This is a prerequisite for improving personalized treatment and ultimately better patient outcomes. Potential tumor subtypes can be identified with methods such as unsupervised clustering or network-based stratification, which assign patients to sets based on high-dimensional molecular profiles. Detailed characterization of identified sets and their interpretation, however, remain a time-consuming exploratory process. To address these challenges, we have developed StratomeX (http://stratomex.caleydo.org), an interactive visualization tool that complements algorithmic approaches. StratomeX also integrates a computational framework for query-based guided exploration directly into the visualization, enabling discovery of novel relationships between patient sets and efficient generation and refinement of hypotheses about tumor subtypes. StratomeX enables analysts to efficiently compare multiple patient stratifications, to correlate patient sets with clinical information or genomic alterations, and to view the differences between molecular profiles across patient sets.

Ciencias

Guided visual exploration
of patient stratiﬁcations in
cancer genomics
Nils Gehlenborg
Harvard Medical School 
Center for Biomedical Informatics
nils_gehlenborg

INTERPRETATION
GENERATIONCOMPUTATION
Machine
Human
Data

“In every chain of reasoning, the evidence of the last conclusion can
be no greater than that of the weakest link of the chain, whatever
may be the strength of the rest.”
- Thomas Reid, Essays on the Intellectual Powers of Man (1786)

INTERPRETATION
GENERATIONCOMPUTATION
Machine
Human
Data
Hypotheses
Discoveries
Knowledge
Cognition

x y1 y2
1.00 0.96 0.76
2.00 0.76 -0.14
3.00 -0.14 -0.91
4.00 -0.91 -0.84
5.00 -0.84 0.00
6.00 0.00 0.84
7.00 0.84 0.91
8.00 0.91 0.14
9.00 0.14 -0.76
10.00 -0.76 -0.96
11.00 -0.96 -0.28

INTERPRETATION
GENERATIONCOMPUTATION
Machine
Human
Hypotheses
Discoveries
Knowledge
Data
Cognition

mRNA expression
microRNA expression
DNA methylation
protein expression
copy number variants
mutation calls
clinical parameters

StratomeX
A Lex, M Streit, H-J Schulz, C Partl, D Schmalstieg, PJ Park, N Gehlenborg, “StratomeX: Visual Anal-
ysis of Large-Scale Heterogeneous Genomics Data for Cancer Subtype Characterization“, Computer
Graphics Forum 31:1175-1184 (2012)
M Streit, A Lex, S Gratzl, C Partl, D Schmalstieg, H Pﬁster, PJ Park, N Gehlenborg, “Guided Visual
Exploration of Genomic Stratiﬁcations in Cancer“, Nature Methods 11:884-885 (2014)

Comparing Patient Sets
across StratiﬁcationsPROBLEM 1

Comparing Patient Sets
within StratiﬁcationsPROBLEM 2

Finding Relevant
Stratiﬁcations and PathwaysPROBLEM 3

Knowledge-driven Exploration
Data-driven Exploration

Query
Rank
Visualize
Stratiﬁcations
Clinical Params
Pathways
Guided Exploration

LineUp
S Gratzl, A Lex, N Gehlenborg, H Pﬁster and M Streit, “LineUp: Visual Analysis of Multi-Attribute
Rankings“, IEEE Transactions on Visualization and Computer Graphics 19:2277-2286 (2013)

Domino
S Gratzl, N Gehlenborg, A Lex, H Pﬁster and M Streit, “Domino: Extracting, Comparing, and
Manipulating Subsets across Multiple Tabular Datasets“, IEEE Transactions on Visualization and
Computer Graphics (2014)

MD Anderson Cancer Center
University of Rostock
Peter J Park
Michael S Noble, David Heiman, Firehose Team, Gad Getz
Terrence Wu, Ian Watson, Lynda Chin
Harvard Medical School
Broad Institute of MIT & Harvard
Christian Partl, Dieter SchmalstiegGraz University of Technology
Johannes Kepler University Linz Samuel Gratzl, Marc Streit
Hans-Jörg Schulz
Acknowledgements
Harvard SEAS Alexander Lex, Hanspeter Pﬁster
Funding
NIH/NHGRI K99 HG007583 Pathway to Independence

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Mustard, as a crop, is susceptible to a variety of pests that can affect its growth and yield. Here’s a rundown of some common pests that target mustard plants: Aphids: These small, sap-sucking insects can cause significant damage by feeding on the leaves and stems. Aphids also excrete a sticky substance known as honeydew, which can lead to the growth of sooty mold on the plants. Flea Beetles: These tiny beetles jump like fleas when disturbed and chew small holes in the leaves. They are particularly damaging in the early growth stages of the plant. Cabbage Loopers: The larvae of a type of moth, these caterpillars are known for their distinctive looping movement. They chew large holes in the leaves and can defoliate plants if present in large numbers. Diamondback Moth Larvae: Another caterpillar pest, these larvae chew small holes in the leaves and can cause extensive damage, especially when infestations are heavy. Whiteflies: These are tiny, winged insects that feed on plant sap and can quickly become a problem in greenhouse or close planting conditions. Like aphids, they also secrete honeydew. Cutworms: These are the larvae of certain types of moths and are known for cutting young plants at the stem base at ground level. They are most destructive during the night. Root Maggots: The larvae of root maggot flies, these pests attack the roots of mustard plants, causing wilting and potentially killing young plants. Harlequin Bugs: These are colorful stink bugs that suck the sap from mustard plant stems and leaves, causing the leaves to become stippled, wilt, and eventually die if the infestation is severe. Mustard Sawfly: The larvae of the mustard sawfly can cause considerable defoliation, as they feed voraciously on the leaves. Clubroot: Caused by a fungus-like organism, clubroot affects the roots, causing them to swell and distort. While technically a disease, it is often associated with pest management because controlling it involves similar preventative strategies. Control Measures: Managing pests in mustard involves a combination of cultural, biological, and chemical methods. Crop rotation, resistant varieties, timely sowing, maintaining plant health, and using natural predators like ladybugs and parasitic wasps can help keep pest populations under control. Chemical pesticides should be used as a last resort due to their potential impact on the environment and non-target species.

Pests of mustard_Identification_Management_Dr.UPR.pdf

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Conjugation, transduction and transformation

Areesha Ahmad

CELL -Structural and Functional unit of life.pdf

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The computation of anti-derivatives is just an in-tellectual challenge, we know how to take deriv-atives, but … can we invert the process? We call this Computing the indefinite integral . In the last presentation we have seen a few indefinite integrals (we called them bricks), but they did not include the anti-derivative of many functions! We are going to try and do better !

COMPUTING ANTI-DERIVATIVES(Integration by SUBSTITUTION)

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Module for Grade 9 for Asynchronous/Distance learning

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Guided visual exploration of patient stratifications in cancer genomics

1. Guided visual exploration of patient stratiﬁcations in cancer genomics Nils Gehlenborg Harvard Medical School  Center for Biomedical Informatics nils_gehlenborg

2. Machine Human

3. Machine Human

4. Machine Human Data

5. INTERPRETATION GENERATIONCOMPUTATION Machine Human Data

6. “In every chain of reasoning, the evidence of the last conclusion can be no greater than that of the weakest link of the chain, whatever may be the strength of the rest.” - Thomas Reid, Essays on the Intellectual Powers of Man (1786)

7. INTERPRETATION GENERATIONCOMPUTATION Machine Human Data Hypotheses Discoveries Knowledge Cognition

8. x y1 y2 1.00 0.96 0.76 2.00 0.76 -0.14 3.00 -0.14 -0.91 4.00 -0.91 -0.84 5.00 -0.84 0.00 6.00 0.00 0.84 7.00 0.84 0.91 8.00 0.91 0.14 9.00 0.14 -0.76 10.00 -0.76 -0.96 11.00 -0.96 -0.28

9. -1 -0.5 0 0.5 1 1 2 3 4 5 6 7 8 9 10 11

10. INTERPRETATION GENERATIONCOMPUTATION Machine Human Hypotheses Discoveries Knowledge Data Cognition

11. INTERPRETATION GENERATIONCOMPUTATION Machine Human Hypotheses Discoveries Knowledge Data| Cognition

12. ?

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14. TCGAThe Cancer Genome Atlas

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16. mRNA expression microRNA expression DNA methylation protein expression copy number variants mutation calls clinical parameters

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22. Stratome

23. Anthony92931 / Wikimedia Commons

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26. StratomeX A Lex, M Streit, H-J Schulz, C Partl, D Schmalstieg, PJ Park, N Gehlenborg, “StratomeX: Visual Anal- ysis of Large-Scale Heterogeneous Genomics Data for Cancer Subtype Characterization“, Computer Graphics Forum 31:1175-1184 (2012) M Streit, A Lex, S Gratzl, C Partl, D Schmalstieg, H Pﬁster, PJ Park, N Gehlenborg, “Guided Visual Exploration of Genomic Stratiﬁcations in Cancer“, Nature Methods 11:884-885 (2014)

27. Comparing Patient Sets across StratiﬁcationsPROBLEM 1

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37. Comparing Patient Sets within StratiﬁcationsPROBLEM 2

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49. Finding Relevant Stratiﬁcations and PathwaysPROBLEM 3

50. ?

51. Knowledge-driven Exploration Data-driven Exploration

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53. Query Rank Visualize Stratiﬁcations Clinical Params Pathways Guided Exploration

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55. LineUp S Gratzl, A Lex, N Gehlenborg, H Pﬁster and M Streit, “LineUp: Visual Analysis of Multi-Attribute Rankings“, IEEE Transactions on Visualization and Computer Graphics 19:2277-2286 (2013)

56. Query Rank Visualize Stratiﬁcations Clinical Params Pathways Guided Exploration

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59. INTERPRETATION GENERATIONCOMPUTATION Machine Human Hypotheses Discoveries Knowledge Data| Cognition

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61. www.caleydo.org

62. www.caleydo.org

63. www.caleydo.org

64. Domino S Gratzl, N Gehlenborg, A Lex, H Pﬁster and M Streit, “Domino: Extracting, Comparing, and Manipulating Subsets across Multiple Tabular Datasets“, IEEE Transactions on Visualization and Computer Graphics (2014)

65. MD Anderson Cancer Center University of Rostock Peter J Park Michael S Noble, David Heiman, Firehose Team, Gad Getz Terrence Wu, Ian Watson, Lynda Chin Harvard Medical School Broad Institute of MIT & Harvard Christian Partl, Dieter SchmalstiegGraz University of Technology Johannes Kepler University Linz Samuel Gratzl, Marc Streit Hans-Jörg Schulz Acknowledgements Harvard SEAS Alexander Lex, Hanspeter Pﬁster Funding NIH/NHGRI K99 HG007583 Pathway to Independence

Guided visual exploration of patient stratifications in cancer genomics

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Guided visual exploration of patient stratifications in cancer genomics