Gene Mapping is the graphic representation of the arrangement of a gene or a DNA sequence on a chromosome. Also known as linkage mapping, it is used to locate and identify the gene or group of genes that determines a particular inherited trait.
The [course_title] course teaches linkage disequilibrium mapping that helps you to analyse non-familial data. Basic concepts of genetic variations will also be discussed in the course.
Prior knowledge of statistical tests and estimation is required.
Course Curriculum
Module: 01 | |||
Introdução ao CSV | 00:02:00 | ||
CSVs in Python | 00:03:00 | ||
修正数据类型 | 00:03:00 | ||
Questions about Student Data | 00:01:00 | ||
Investigating the Data – Solution | 00:02:00 | ||
Problems in the Data | 00:01:00 | ||
Missing Engagement Records 12 | 00:01:00 | ||
Missing Engagement Records | 00:01:00 | ||
Checking for More Problem Records | 00:01:00 | ||
找到剩余问题 | 00:01:00 | ||
Module: 02 | |||
Refining the Question | 00:03:00 | ||
Getting Data from First Week | 00:01:00 | ||
满足好奇心 | 00:01:00 | ||
探索学员参与度 | 00:04:00 | ||
Number of Visits in the First Week | 00:02:00 | ||
Splitting out Passing Students | 00:01:00 | ||
Comparing the Two Student Groups | 00:01:00 | ||
Making Histograms – Solution | 00:02:00 | ||
Seus Resultados são Apenas Sujeira? | 00:01:00 | ||
A correlação não implica a causa | 00:03:00 | ||
Module: 03 | |||
Previsão baseada em muitas características | 00:01:00 | ||
沟通 | 00:01:00 | ||
Improving Sharing Plots – Solution | 00:01:00 | ||
数据分析与相关术语 | 00:02:00 | ||
Conclusão | 00:01:00 | ||
Dados Uni-Dimensional em NumPy e Pandas | 00:02:00 | ||
NumPy Arrays – Solution | 00:04:00 | ||
+ vs. += Solution | 00:01:00 | ||
In-Place vs. Not In-Place | 00:01:00 | ||
Series Indexes – Solution | 00:01:00 | ||
Module: 04 | |||
Vectorized Operations and Series Indexes | 00:01:00 | ||
Filling Missing Values | 00:02:00 | ||
Pandas Series apply() – Solution | 00:01:00 | ||
Plotting in Pandas – Solution | 00:01:00 | ||
Conclusion 12345 | 00:01:00 | ||
Subway Data | 00:01:00 | ||
Subway Data – Solution | 00:01:00 | ||
Two-Dimensional NumPy Arrays – Solution | 00:02:00 | ||
Two-Dimensional NumPy Arrays – Solution | 00:02:00 | ||
NumPy Axis | 00:01:00 | ||
Module: 05 | |||
NumPy Axis – Solution | 00:01:00 | ||
Accessing Elements of a DataFrame | 00:02:00 | ||
Accessing DataFrame Elements – Solution | 00:02:00 | ||
CSVs in Python – Solution | 00:02:00 | ||
Questions about Student Data – Solution | 00:02:00 | ||
Missing Engagement Records – Solution | 00:01:00 | ||
More Problem Records – Solution | 00:01:00 | ||
Refining the Question – Solution | 00:01:00 | ||
Getting Data from First Week – Solution | 00:01:00 | ||
Debugging Data Analysis Code – Solution | 00:02:00 | ||
Module: 06 | |||
Lessons Completed in First Week | 00:01:00 | ||
Number of Visits – Solution | 00:02:00 | ||
Splitting Students – Solution | 00:02:00 | ||
Comparing Student Groups – Solution | 00:03:00 | ||
Gapminder Data – Solution | 00:01:00 | ||
NumPy Index Arrays – Solution | 00:01:00 | ||
Multiplying by a Scalar – Solution | 00:01:00 | ||
Overall Completion Rate – Solution | 00:01:00 | ||
Standardizing Data – Solution | 00:01:00 | ||
NumPy Index Arrays – Solution | 00:01:00 | ||
Module: 07 | |||
+ vs. += | 00:01:00 | ||
In-Place vs. Not In-Place | 00:01:00 | ||
Pandas Series – Solution | 00:02:00 | ||
Series Indexes | 00:03:00 | ||
Series Vectorized Operations – Solution | 00:02:00 | ||
Filling Missing Values – Solution | 00:01:00 | ||
apply() Example | 00:04:00 | ||
Sons Of The East – Into The Sun [Official Video] | 00:05:00 | ||
Loading Data into a DataFrame | 00:01:00 | ||
Calculating Correlation | 00:03:00 | ||
Pandas Axis Names | 00:01:00 | ||
Module: 08 | |||
DataFrame Vectorized Operations | 00:01:00 | ||
Vectorized Operations – Solution | 00:02:00 | ||
DataFrame applymap() | 00:01:00 | ||
DataFrame applymap() – Solution | 00:01:00 | ||
DataFrame apply() Use Case 2 | 00:01:00 | ||
DataFrame apply() – Solution | 00:01:00 | ||
DataFrame apply() Use Case 2 | 00:01:00 | ||
DataFrame apply() Use Case 2 – Solution | 00:02:00 | ||
Adding a DataFrame to a Series | 00:01:00 | ||
Standardizing Each Column Again | 00:04:00 | ||
Module: 09 | |||
Combining Pandas DataFrames – Solution | 00:01:00 | ||
Plotting for DataFrames – Solution | 00:02:00 | ||
Conclusão | 00:01:00 | ||
Assessment | |||
Submit Your Assignment | 00:00:00 | ||
Certification | 00:00:00 |
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