Dear Members of the South Australian Branch of the Statistical Society.
Date: WEDNESDAY 22 MARCH 2017
Time: 5.30 for 6.05 pm
Venue: University of Adelaide, North Terrace
Room: Engineering North N132
Campus map is available at http://www.adelaide.edu.au/campuses/northtce/ .
Election of Returning Officer, Branch officers, Council and Public Officer
Please note only financial members of the society will be eligible to vote in person, or by proxy.
While a number of council members are willing to stand for office again, this is a first call for nominations for the positions of:
President, Vice-President, Secretary and Treasurer and, Councillor positions assist in the following tasks related to local activities and the relationship with the central SSAI:
Newsletter correspondent, Young Stats organiser(s), Website coordinator, Speaker program manager.
Nominations are called for all positions and may be communicated to the Secretary Paul Sutcliffe ([email protected] or 0438446064) before the meeting or may be made from the floor at the meeting.
AGENDA – ANNUAL GENERAL MEETING
2. Minutes of the 2016 Annual General Meeting
3. Annual Report
4. Election of Returning Officer, Branch officers, Council and Public Officer
5. Treasurers Report
6. Election of Auditor
7. Any other business
9. Speakers: Sarah James & Daniel Kon – University of Adelaide.
Dinner: After the AGM, all are welcome to adjourn with the speaker to Lemongrass, Thai restaurant, 289 Rundle Street, Adelaide.
Please rsvp for dinner to [email protected] by 20th March 2017.
Speakers: Sarah James & Daniel Kon – University of Adelaide.
Title: DNA sequence estimation using alignment and quality data
Abstract: Phylogenetics is an area of study concerning the evolutionary relationships between individuals or species. Investigations of these relationships often use ancient DNA sequences, as well as modern DNA sequences. Ideally, the DNA sequencing process would be perfect. However, when we sequence DNA, the sequencing process may introduce errors and slightly affect the quality of the sequences. Churchill and Waterman describe a method that estimates the sequencing errors and the consensus sequence based only on the sequence reads contained within the alignment matrix. In this talk, I will summarise Churchill and Waterman’s method and discuss how we have improved their method by including quality scores associated with each read and allowing for missing data in the alignment matrix.
Biography: Sarah completed a Bachelor of Mathematical Sciences in Statistics and Applied Mathematics at the University of Adelaide. She is currently in her second year of Masters (Statistics) at the University of Adelaide, looking into missing data in phylogenetic data sets.
Title: Models of Missingness in Mass Spectrometry Data
Abstract: Gastric cancer is a disease with a poor prognosis owing to the difficulty of early-stage detection. Matrix assisted laser desorption/ionisation time of flight (MALDI-TOF) mass spectrometry (MS) is a technology involved in the discovery of proteomic biomarkers that correlate with disease states. It is hoped these proteomic biomarkers may be used for future non-invasive, sensitive, and specific diagnostic tests. A hurdle in the use of MALDI-TOF MS is the large proportion of missing values in the output datasets. This missingness is nonignorable and may bias parameter estimates, hampering the discovery of biomarkers or leading to the erroneous identification of proteins that are not valid biomarkers. In this presentation I investigate a MALDI-TOF MS dataset created by the Adelaide Proteomic Centre with the aim of modelling the missingness pattern. This work will lead into a joint model for missing and observed data that, by accounting for missingness mechanisms, can model protein expression values with reduced bias, leading to improved biomarker discovery over existing methods of analysis.
Biography: Daniel is a second-year Masters (Statistics) student at the University of Adelaide. His supervisor is Professor Patty Solomon and his research topic is about modelling response-dependent missingness in data from proteomic mass spectrometry experiments.
Statistical Society of Australia
Tel. 0438 446 064
|Time:||5:30 pm - 7:00 pm|
|Location:||Engineering North N132, University of Adelaide,