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SATuRN HIV-1 Genotyping System. Justen Manasa Africa Centre for Health and Population Studies Virology laboratory based at the Nelson R. Mandela School of Medicine University of KwaZulu Natal. SATuRN.
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SATuRN HIV-1 Genotyping System Justen Manasa Africa Centre for Health and Population Studies Virology laboratory based at the Nelson R. Mandela School of Medicine University of KwaZulu Natal
SATuRN • A collaborative network of scientists and researchers working on HIV and TB drug resistance.
Collaborative SATuRN version (currently 3000 patients with genotype information). Users: • AC-UKZN (Dr. Tulio de Oliveira). • MRC and Jembi Health Systems (Dr. Chris Seebregts) • HPP Virology, University of KwaZulu-Natal (Dr. Mitchell Gordon) • Stellenbosh Univ. (Dr. Gert Van Zyl), • NICD (Prof. Lynn Morris, Dr. Gillian Hunt), • NHLS, Witts University (Prof Wendy Stevens/Prof Maria Papathanasopoulos) • Inkhosi Albert Luthuli Department of Virology Laboratory NHLS (Dr. Pravi Moodely) • UFS (Dr. Cloete van Vurren, Dewald Stein), • Pretoria Univ. (Prof. Sharon Cassol and Theresa Russouw), • Dept of Medical Virology, University of Pretoria (Prof. Sheila Bowyer/Prof Lynne Webber) • Ministry of Health (Botswana) (Dr. Madisa Mine and Dr. Avalos) • AIDS and TB Unit -Ministry of Health (Zimbabwe) • Stanford-UZ (Prof. David Katzenstein), Policy: • No private patient information or public identification number is added to the database. • Data is owned by the researchers. • Database is password protected and datasets and dataset access is exclusive to the researcher. Researcher can give access to part of the data to its collaborators. • After publication researchers can choose to deposit the data in a collaborative area “public area” of the database where other participants of the network have access to the data. • Publication of manuscripts from “public” area will include as authors up to two members of the group that deposited data.
Data Entries at AC + clinical and treatment info RegaDB database at MRC Sequence Analysis At AC Lab
RT-PCR Protocol Protease and RT Reverse transcription RT21 1st Round PCR MAW26 RT21 2nd Round PCR RT20 Pro1 1.3 kb fragment
SATuRN Data Curation Stanford HIVDB SATuRN DB Collaborators • Input data • Sequences • Clinical data • Tx history • Viral load and CD4 results Data Curation Rega DB Data Curation At Stanford PASSWORD PROTECTION OF Rega DB HIVDB Mirror HIVDB
REGA DATABASE (RegaDB) • A medical informatics database dedicated to HIV management • Linked to a some of the leading HIV drug resistance analysis tools • Can be used as either a clinical or research tool • The online version provides a very good collaborative platform • To be used by • Clinicians • Researchers • Data is password protected • All data is de-identified • Data can be published thus accessible to other members of the consortium or unpublished-access limited to the owners only. Developed by: REGA Institute, Leuven and Mybiodata
RegaDB Objective • A free and open-source database system • Facilitate research collaborations • Easily interchange data, keeping track of data origin • Create collaborative databases keeping track of dataset versions • Easily publish data sets to Stanford HIVDB • Empower clinicians with analysis tools • Patient history graph • Sequence analyses • HIV typing and subtyping • Genotypic analyses for resistance interpretation • Third party analyses as “web services” • Resistance reports
Data Entities Event Therapy Attribute Patient Dataset Viral Isolate Test
Attributes • Annotate Patient with information • Adapts to “your (research) interest” • Typically clinical and epidemiological information • Examples • Gender • HIV transmission risk group • Most of information collected in Collaborative projects • Attributes may be grouped (like “SATuRN or SPREAD”)
Viral Isolates Viral Isolates Nucleotide Sequence A N A L Y S E S Amino Acid Sequence Information automatically inferred Insertion Mutation Protein
Analysis Services • Built-in services • REGA Subtype tool • Stanford ASI genotypic resistance algorithms • ANRS, HIVDB, REGA • Resistance report generation • Using your own template documents • Integrate with external analysis services • Using “web services” • e.g. connect to geno2pheno or Stanford
Synchronize auxiliary data • Auto-update services for • Drug definitions • New (versions of) resistance algorithms • Test types / Tests • Attribute types / Attribute groups