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The course represents all the training materials for the BMMB:852 Applied Bioinformatics course offered at Penn State in 2017.
The course offers a structured path through the Biostar Handbook. Various sections of the book are presented via smaller, logical consistent units. We recommend learning two-four units per week.
The lectures consist of slides, links to various chapters, links to supporting materials and homework. There are no videos.
Please consult the synopsis for details on what is covered and how to learn the materials.
Note: This book follows the 1st edition of the Handbook and will not match the content of the 2nd Edtion. There may be links and content that refer to sections that have been moved. For up to date content see Applied Bioinformatics (2020)
Lecture | Your Score |
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Lecture 1: How is Bioinformatics practiced?
Course structure. How is bioinformatics practiced. Computer setup. |
Test |
Lecture 2: How do I use the command line?
Unix command line use. Find help on commands. Flag system. |
Test |
Lecture 3: How are Unix commands used for data analysis?
Examples of processing biological data from the command line. |
Test |
Lecture 4: What do the words mean?
How to make sense of terminology. Sequence and gene ontologies. |
Test |
Lecture 5: How to interpret a list of genes?
Functional enrichment, functional over-representation. |
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Lecture 6: How to access published data from the command line
Reproducibility. Data repositories. Entrez Direct |
Test |
Lecture 7: Data formats. Genbank, FASTA and FASTQ
Accessing and manipulating sequencing data. |
Test |
Lecture 8: Quality control of high throughput sequencing data
Quality visualization. Improving data quality. Adapter removal. |
Test |
Lecture 9: Advanced quality control of FASTQ data
Sequence duplication, read merging, MultiQC, error correction. |
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Lecture 10: Sequencing concepts, methods, coverage formula
Single end and paired-end sequencing, computing sequencing depth |
Test |
Lecture 11: Scripting and Automation
Automating tasks. Make analyses reproducible. |
Test |
Lecture 12: Accessing the Short Read Archive
Short read archive, fastq-dump, repeating commands |
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Lecture 13: Sequence Alignments
Alignment scoring, global, local alignments |
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Lecture 14: BLAST, Basic Local Alignment Search Tool
Using blast online and at the command line |
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Lecture 15: BLAST databases
Make blast databases. BLAST search tasks. |
Test |
Lecture 16: Short Read Aligners
What is short read alignment. How to run bwa and bowtie2. |
Test |
Lecture 17: Sequence Alignment Maps (SAM)
SAM/BAM the workhorse of high throughput sequencing |
Test |
Lecture 18: Paired end reads in BAM files.
Create and filter BAM files. |
Test |
Lecture 19: Visualizing BAM alignments
How to use IGV |
Test |
Lecture 20: Visualizing Large Genomic Variation
Large insertions, deletions, copy number variations |
Test |
Lecture 21: Filtering SAM files
Select alignments by their attributes |
Test |
Lecture 22: Processing SAM/BAM files
Picard tools. Unaligned BAM files. |
Test |
Lecture 23: Short Genomic Variations
First steps in detecting short variations |
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Lecture 24: Let's call some SNPs
SNP calling with bcftools and freebayes |
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Lecture 25: The Variant Call Format
Understand the VCF format. |
Test |
Lecture 26: Making sense of variants
variant effect prediction, interval datatypes, BED, GFF |
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Lecture 27: Sequencing Application Domains
Re-sequencing, assembly, classification |
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Lecture 28: Quantifying with sequencing
Functional assays, computing coverages over intervals |
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Lecture 29: Introduction to RNA-Seq data analysis
RNA-Seq concepts |
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Lecture 30: RNA-Seq statistical analysis
Lecture 30 |
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Course Synopsis: How does this course work?
What is the structure and purpose of this course. |
Test |