Upcoming SciNet Events

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August,2020
Tue 11th Aug
12:30 pm
2:00 pm
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Learn parallel programming R, with a focus on parallel data analysis. Location: SciNet Online
Wed 12th Aug
12:30 pm
2:00 pm
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Learn parallel programming R, with a focus on parallel data analysis. Location: SciNet Online
Thu 13th Aug
12:30 pm
2:00 pm
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Learn parallel programming R, with a focus on parallel data analysis. Location: SciNet Online
Tue 18th Aug
12:30 pm
2:00 pm
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Learn how to perform data cleaning and statistical analysis of large scale genetic data using PLINK and R software. We will use SciNet to run the PLINK analytical workflow to perform markers and individuals quality control, including population stratification and ancestry followed by association analysis between genetic variation and trait of interest. R-software (basic R plotting and ggplot package) will be use to visualize the results. Location: SciNet Online
Wed 19th Aug
12:30 pm
2:00 pm
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Learn how to perform data cleaning and statistical analysis of large scale genetic data using PLINK and R software. We will use SciNet to run the PLINK analytical workflow to perform markers and individuals quality control, including population stratification and ancestry followed by association analysis between genetic variation and trait of interest. R-software (basic R plotting and ggplot package) will be use to visualize the results. Location: SciNet Online
Thu 20th Aug
12:30 pm
2:00 pm
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Learn how to perform data cleaning and statistical analysis of large scale genetic data using PLINK and R software. We will use SciNet to run the PLINK analytical workflow to perform markers and individuals quality control, including population stratification and ancestry followed by association analysis between genetic variation and trait of interest. R-software (basic R plotting and ggplot package) will be use to visualize the results. Location: SciNet Online
Tue 25th Aug
12:30 pm
2:00 pm
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Debugging and profiling are important steps in developing a new code, or porting an old one to a new machine. In this session, we will discuss the debugging of frequently encountered bugs in serial code with gdb and the debugging of parallel (MPI and threaded) codes. Location: SciNet Online
Wed 26th Aug
12:30 pm
2:00 pm
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Debugging and profiling are important steps in developing a new code, or porting an old one to a new machine. In this session, we will discuss the debugging of frequently encountered bugs in serial code with gdb and the debugging of parallel (MPI and threaded) codes. Location: SciNet Online
Thu 27th Aug
12:30 pm
2:00 pm
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Debugging and profiling are important steps in developing a new code, or porting an old one to a new machine. In this session, we will discuss the debugging of frequently encountered bugs in serial code with gdb and the debugging of parallel (MPI and threaded) codes. Location: SciNet Online
September,2020
Tue 8th Sep
11:00 am
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This course is to introduce graduate students to the programing language Python. The course will teach the students how to install Python on their laptop and then use Python to perform data analysis. The course consists of twelve hands-on sessions, each lasting one hour, where students bring their own laptops and perform assignments, each of these assignments being due for the following lecture. Part of Introduction to Programming in Python
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Tue 8th Sep
12:00 pm
1:30 pm
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In this course data analysis techniques utilizing the R statistical language, will be discussed and introduced, as well as, the basics of programming and scientific computing.The goal of this course is to prepare graduate students to perform scientific data analysis. Successful students will learn how to use statistical inference tools to gain insight into large and small data sets, as well as be exposed to cutting-edge techniques and best practises to store, manage and analyze (large) data.Topics include: R programming, version control, automation, modular programming and scientific visualization.Students willing to take the course as part of their graduate program have to enroll through Acorn/ROSI.This course is part of the IMS graduate program and due to be current CoViD19 pandemic, it will be taught fully online. Location: SciNet Online
Thu 10th Sep
12:00 pm
1:30 pm
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In this course data analysis techniques utilizing the R statistical language, will be discussed and introduced, as well as, the basics of programming and scientific computing.The goal of this course is to prepare graduate students to perform scientific data analysis. Successful students will learn how to use statistical inference tools to gain insight into large and small data sets, as well as be exposed to cutting-edge techniques and best practises to store, manage and analyze (large) data.Topics include: R programming, version control, automation, modular programming and scientific visualization.Students willing to take the course as part of their graduate program have to enroll through Acorn/ROSI.This course is part of the IMS graduate program and due to be current CoViD19 pandemic, it will be taught fully online. Location: SciNet Online