Linked2Safety Project (FP7-ICT-2011-7 – 5.3)A NEXT-GENERATION, SECURE LINKED DATA MEDICAL INFORMATION SPACE FOR

SEMANTICALLY-INTERCONNECTING ELECTRONIC HEALTH RECORDSAND CLINICAL TRIALS SYSTEMS

ADVANCING PATIENTS SAFETY IN CLINICAL RESEARCH

12th International Conference on Bioinformatics and Bioengineering, Larnaka

The effects of applying cell-suppression andperturbation to aggregated genetic data

Athos Antoniades, John Keane, Aristos Aristodimou, Christa Philipou, Andreas Constantinou, Christos Georgousopoulos, Federica Tozzi, Kyriacos Kyriacou, Andreas Hadjisavas, Maria Loizidou, Christiana Demitriou and Constantinos

Pattichis

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Introduction

Why Share Data? What are the current legal and ethical

limitations? How have scientists shared medical data so far? Key Problems Perturbation Cell Suppression

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The Problem

Why share data:Replication TestingStatistical PowerMultiple Testing Problem

Legal and Ethical IssuesAnonymization vs PseudoanonimizationLimitations derived from consent form signed by subjectsOther, regional, study, or subject specific issues.

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How have scientists shared medical data Contingency Table and Data Cube

example

  aa aA AA

Case U00 U01 U02

Control U10 U11 U12

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16 year old widow Problem

A paper that analyzes data from a specific study reports:

Marital Status

Age

Age Married Widowed Single0-16 0 1 5018-24 10 5 5025-34 40 7 4035~ 60 15 20

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16 year old widow Problem

A paper that analyzes data from a specific study reports:

Marital Status

Age

Age Married Widowed Single0-16 0 1 5018-24 10 5 5025-34 40 7 4035~ 60 15 20

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16 year old widow Problem

A paper that analyzes data from a specific study reports:

Marital Status

Age

Age Married Widowed Single0-16 0 1 5018-24 10 5 5025-34 40 7 4035~ 60 15 20

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Categorization Differences

Paper 1 that analyzes data from a specific

study reports:Marital Status

Age

Age MarriedWidowe

d Single0-16 NA NA 5018-24 10 7 5025-34 40 7 4035~ 60 15 20

Marital Status

Age

Age MarriedWidowe

d Single0-16 NA NA 5018-25 10 8 5026-35 45 7 4036~ 55 14 20

Paper 2 that analyzes data from the same

study reports:

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Perturbation and Cell Suppression

Original Data

Marital Status

Age

Age MarriedWidowe

d Single0-16 0 1 5018-24 10 7 5025-34 40 7 4035~ 60 15 20

Marital Status

Age

Age MarriedWidowe

d Single0-16 NA NA 5118-24 9 8 4925-34 40 7 4135~ 61 14 21

Perturbation (+-1) andCell Suppression (<5)

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Evaluation

• Most common parameters testedPerturbation:[0], [-1,1], [-3,3], [-5,5], [-10,10]Cell Supression: <0, <=1, <=3,<=5,<=10

• Standard main effect test using Chi Square

• Pearson’s Correlation Coefficient used to evaluate deviation of each parameter combination to original results.

• A-priory defined threshold for Pearson’s correlation coefficient <=0.95.

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Evaluating Parameters with a matrix of graphs

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Conclusion and Future Work

We were able to identify for this dataset, the maximum noise that can be added to the data without significantly affecting the outcomes.

Results only relevant to MASTOS, all other datasets need to repeat the analytical approach described.

Further investigation is necessary to identify the minimum parameter settings to satisfy legal and ethical requirements.

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Who to Contact

Athos AntoniadesUniversity of Cyprus

email: athos@cs.ucy.ac.cy