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Systematic temporal analysis of transcriptomic datasets using TrendCatcher identifies early and persistent neutrophil activation as a hallmark of severe COVID-19

Safe People

Organisation name

University of Illinois Chicago

Applicant name(s)

Jalees Rehman

Safe Projects

Project ID

DAA110_EGA

Lay summary

Cells respond to infections by changing the levels of genes. These changes can occur rapidly or slowly, sometimes genes increase and then decrease. We are developing a software program called TrendCatcher that finds the genes which change the most over time. We are especially interested in how COVID-19 changes genes in blood cells over time. By finding the genes that change the earliest, we may be able to understand which patients with COVID-19 will do well and which ones may do poorly. By identifying the patients who are the most vulnerable, one could start treating them early to prevent them from becoming very ill.

Request category type

Research

Other approval committees

NIHR BioResource Data Access Committee

Latest approval date

21/03/2022

Safe Data

Dataset(s) name
Data sensitivity level

De-Personalised

Legal basis for provision of data under Article 6

(e) processing is necessary for the performance of a task carried out in the public interest or in the exercise of official authority vested in the controller;

Lawful conditions for provision of data under Article 9

(j) processing is necessary for archiving purposes in the public interest, scientific or historical research purposes or statistical purposes in accordance with Article 89(1) based on Union or Member State law which shall be proportionate to the aim pursued, respect the essence of the right to data protection and provide for suitable and specific measures to safeguard the fundamental rights and the interests of the data subject.

Common Law Duty of Confidentiality

The individual to whom the information relates has consented

National data opt-out applied?

No

Request frequency

One-off

Safe Setting

Access type

Release