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1. Biology of RNA and Next Generation Sequencing 4
Learn about the process of gene expression, alternative splicing and assays for mRNA detection and quantification
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Lecture1.1
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Lecture1.2
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Lecture1.3
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Quiz1.1
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2. Processing RNA-seq data and generating a table of expression 3
Learn about Next Generation Sequencing and the steps to analyze and interpret RNA-seq data
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Lecture2.1
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Lecture2.2
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Quiz2.1
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3. Understanding The Table of Expression 3
Learn about working with the table of expression to get a high-level view of RNA-seq data
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Lecture3.1
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Lecture3.2
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Assignment3.1
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4. Conclusion and Additional Resources 3
Additional resources for reading to review what we learned in Transcriptomics 1
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Lecture4.1
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Lecture4.2
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Assignment4.1
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5 Comments
why is FASTQ format preferred over FASTA format?
FastQ has quality of sequencer incorporated into the format:
FastA are text files containing multiple DNA* seqs each with some text, some part of the text might be a name.
FastQ files are like fasta, but they also have quality scores for each base of each seq, making them appropriate for reads from an Illumina machine (or other brands)
SAM holds an alignment of seqs w/qual scores against a template.
BAM is a compressed binary format for SAM, however it can also be unaligned in which case it’s more like a compressed version of fastq.
Should the reads for TopHat algorithm be pair-end reads or single-end ?
tanto faz 😉
It’s will change comand line of the TopHat.
VERY GOOD EXPLAINING…STUDENTS ARE LEARN BRIGHT YOUR FUTURE I HOPE ITS BETTER