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We will explain how to perform the standard processing and normalization steps, starting with raw data, to get to the point where one can investigate relevant biological questions. Throughout the case studies, we will make use of exploratory plots to get a general overview of the shape of the data and the result of the experiment. We start with RNA-seq data analysis covering basic concepts and a first look at FASTQ files. We will also go over quality control of FASTQ files; aligning RNA-seq reads; visualizing alignments and move on to analyzing RNA-seq at the gene-level : counting reads in genes; Exploratory Data Analysis and variance stabilization for counts; count-based differential expression; normalization and batch effects. Finally, we cover RNA-seq at the transcript-level : inferring expression of transcripts (i.e. alternative isoforms); differential exon usage. We will learn the basic steps in analyzing DNA methylation data, including reading the raw data, normalization, and finding regions of differential methylation across multiple samples. The course will end with a brief description of the basic steps for analyzing ChIP-seq datasets, from read alignment, to peak calling, and assessing differential binding patterns across multiple samples.
Given the diversity in educational background of our students we have divided the series into seven parts. You can take the entire series or individual courses that interest you. If you are a statistician you should consider skipping the first two or three courses, similarly, if you are biologists you should consider skipping some of the introductory biology lectures. Note that the statistics and programming aspects of the class ramp up in difficulty relatively quickly across the first three courses. By the third course will be teaching advanced statistical concepts such as hierarchical models and by the fourth advanced software engineering skills, such as parallel computing and reproducible research concepts.
These courses make up two Professional Certificates and are self-paced:
Data Analysis for Life Sciences:
- PH525.1x: Statistics and R for the Life Sciences
- PH525.2x: Introduction to Linear Models and Matrix Algebra
- PH525.3x: Statistical Inference and Modeling for High-throughput Experiments
- PH525.4x: High-Dimensional Data Analysis
Genomics Data Analysis:
- PH525.5x: Introduction to Bioconductor
- PH525.6x: Case Studies in Functional Genomics
- PH525.7x: Advanced Bioconductor
This class was supported in part by NIH grant R25GM114818.
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Syllabus
- Mapping reads
- Quality assessment of Next Generation Data
- Analyzing RNA-seq data
- Analyzing DNA methylation data
- Analyzing ChIP Seq data
Instructors
Rafael Irizarry
Professor of Biostatistics
Harvard University
Michael Love
Assistant Professor, Departments of Biostatistics and Genetics
UNC Gillings School of Global Public Health
Vincent Carey
Professor, Medicine
Harvard Medical School
Content Designer
Harvard University is a private Ivy League research university in Cambridge, Massachusetts. Established in 1636 and named for its first benefactor clergyman John Harvard, Harvard is the United States' oldest institution of higher learning, and its history, influence, and wealth have made it one of the world's most prestigious universities. The Harvard Corporation is its first chartered corporation. Although never formally affiliated with any denomination, the early College primarily trained Congregational and Unitarian clergy. Its curriculum and student body were gradually secularized during the 18th century, and by the 19th century, Harvard had emerged as the central cultural establishment among Boston elites. Following the American Civil War, President Charles W. Eliot's long tenure (1869–1909) transformed the college and affiliated professional schools into a modern research university; Harvard was a founding member of the Association of American Universities in 1900. A. Lawrence Lowell, who followed Eliot, further reformed the undergraduate curriculum and undertook aggressive expansion of Harvard's land holdings and physical plant. James Bryant Conant led the university through the Great Depression and World War II and began to reform the curriculum and liberalize admissions after the war. The undergraduate college became coeducational after its 1977 merger with Radcliffe College.
The university is organized into eleven separate academic units—ten faculties and the Radcliffe Institute for Advanced Study—with campuses throughout the Boston metropolitan area: its 209-acre (85 ha) main campus is centered on Harvard Yard in Cambridge, approximately 3 miles (5 km) northwest of Boston; the business school and athletics facilities, including Harvard Stadium, are located across the Charles River in the Allston neighborhood of Boston and the medical, dental, and public health schools are in the Longwood Medical Area. The endowment of Harvard's is worth $37.1 billion, making it the largest of any academic institution.
Harvard is a large, highly residential research university. The nominal cost of attendance is high, but the university's large endowment allows it to offer generous financial aid packages. The Harvard Library is the world's largest academic and private library system, comprising 79 individual libraries holding over 18 million items. The University is cited as one of the world's top tertiary institutions by various organizations.
Harvard's alumni include eight U.S. presidents, several foreign heads of state, 62 living billionaires, 359 Rhodes Scholars, and 242 Marshall Scholars. To date, some 157 Nobel laureates, 18 Fields Medalists, and 14 Turing Award winners have been affiliated as students, faculty, or staff. In addition, Harvard students and alumni have won 10 Academy Awards, 48 Pulitzer Prizes, and 108 Olympic medals (46 gold, 41 silver and 21 bronze).
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