• norsk
    • English
  • English 
    • norsk
    • English
  • Login
View Item 
  •   Home
  • Fakultet for medisin og helsevitenskap (MH)
  • Institutt for klinisk og molekylær medisin
  • View Item
  •   Home
  • Fakultet for medisin og helsevitenskap (MH)
  • Institutt for klinisk og molekylær medisin
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

Characterizing viral diversity in Respiratory tract infection: Emphasizing on Microarray technology as genomic sensor in clinical diagnosis

Noreen, Saadia
Master thesis
Thumbnail
View/Open
665966_FULLTEXT01.pdf (3.386Mb)
URI
http://hdl.handle.net/11250/263659
Date
2013
Metadata
Show full item record
Collections
  • Institutt for klinisk og molekylær medisin [2070]
Abstract
Background: Acute respiratory tract infection is common illness of human with significant morbidity and mortality. In pediatrics, viruses are the major cause if this illness. There is an imperative need to develop a diagnostic tool to measure viral diversity for preventing contraproductive treatments. This present study focuses on  evaluating viruses from clinical samples of respiratory tract infection by using advanced diagnostic method such as microarray technology.

Methods: Target was amplified using random amplification. Indirect method of hybridization was used to fluorescently label target with Cy3. A previously developed  LLMDA subarray 2 (GPL13407) was demonstrated as detectichip. This chip comprise of 58,000 probes. The detectichip was designed by Agilent technologies. Samples  were hybridized on this chip. The resulting fluorescent produce after hybridization was explored and digitized using gene pix pro software. Data was normalized with two methods named as 1) within array control method 2) with whole negative control array. Log 2 fold change was calculated. Significant testing was also performed. Detecti V software was used to perform these tasks.

Results: Detected viral species were arranged according to their log2 fold change. The higher log 2 fold change indicated the abundance of viral species in sample. More over graphs and figures were also drawn to indicate the detection of viral species. Significant testing indicates the presence of high level viral families according to their p-value and t testing.

Conclusion: Detectichip can successfully characterize viruses frequently found in clinical samples. By applying both normalization method it can be stated that this detectichip able to identify broad spectrum of viral family, viral species, bacteriophages, plant virus. The likely viral RTI were adenovirus, influenza virus, rhino virus.  The rare virus associated with RTI was human papilloma virus and mammalian orthoreovirus. This chip confirms that in sample 1 adenoviridae family was significantly present where as in sample 2 the likely specie is Influenza .
Publisher
Norges teknisk-naturvitenskapelige universitet, Det medisinske fakultet, Institutt for kreftforskning og molekylær medisin

Contact Us | Send Feedback

Privacy policy
DSpace software copyright © 2002-2019  DuraSpace

Service from  Unit
 

 

Browse

ArchiveCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsDocument TypesJournalsThis CollectionBy Issue DateAuthorsTitlesSubjectsDocument TypesJournals

My Account

Login

Statistics

View Usage Statistics

Contact Us | Send Feedback

Privacy policy
DSpace software copyright © 2002-2019  DuraSpace

Service from  Unit