BINF 511 Lecture Notes - Lecture 12: Cytosine, Alternative Splicing, Biological Process
25 Jun 2018
School
Department
Course
Professor
Lecture 12: Wrap up
April 11, 2018
Regarding the final exam
9 am on April 25th
Centennial Centre, Ballroom
Cumulative
Similar layout as the midterm
1-1.5 hours, but will have the whole 3 hours to complete
There will be 1 question on genome assembly on the final exam, but the exercise will be
ungraded
Need to know long reads versus short reads, sanger sequencing versus next generation
sequencing
As for coding, she will ask what something means, but we will not write code off the top of our
head
Basic Unix skills
How we communicate with computers
Can navigate around the file systems
Can give permissions per file
Know the basic commands
o
Unix shell lets you talk with the machine and send files
Foreach loops help speed things up
Perl/Python
Perl = practical extraction and reporting language
oQuick to program something functional for day to day work
oHigh pattern finding capacity
oHas a lot of mark up (more annotations, more tags)
oShebang line tells the computer that this is perl code and where to find perl (the
interpreter)
Ex: #!/usr/bin/perl
Python: more striped down
Tree of life
Life is complex, so we want to find out more information
find more resources at oneclass.com
find more resources at oneclass.com
Transcription: there are many transcripts coming out from one gene -> this can tell us how much
proteins to expect
Metabolite/metabolomics methods
Refer to the guest lecture
Analysis strategies
Identity/Similarity/Homology
Identity: exactly the same nucleotide or amino acid in the same position in two aligned
sequences (proteins and sequences)
Similarity: when different substitutions are more or less good (proteins)
Homology: relatedness between two sequences (proteins and sequences)
Contig
Know what it is and how we use them (for the final exam)
Depth of a contig = number of overlapping sequences
oThis is a quality measure
oFor Sanger, 10 is good
oFor next generation, need at least 30 (100 is fantastic)
EST contig: overlaps that should cover the whole mRNA
Hybridization based technique (for transcriptomics)
Drawbacks:
find more resources at oneclass.com
find more resources at oneclass.com
oHow to measure gene or genome that is not on array? (rare genes)
oHow to distinguish between close gene copies? (similar genes)
oWhat if expression is higher than when spot is saturated?
oHow to deal with dye bias and background? (bias if gene is not on array)
Know why we use them, the positives, and the negatives, don't need to know how to make
them
cDNA arrays consists of spots of cDNA PCR products
ocDNA array = transcripts/genes
oOverlap two colored images and then do pixel quantification
Basic unit of quantification: pixellated spot
Gene chip = spotted in a different way
Next generation sequencing (as opposed to hybridization techniques)
Sequencing by synthesis
Applications
oDe novo sequencing: any genome
oGenome re-sequencing: map variations across individuals (ex: cancer genome
sequencing, crop cultivars)
oQuantitative biology of complex systems: new high throughput technologies in
functional genomics (ex: ChIP-seq, RNA-seq)
There's no nice program for NGS analysis, need to figure out what you want to do with your
sequence
SAM/BAM
oInput for many software
oNext-gen sequence data tools can use SAM/BAM format
oSAM: sequence alignment/map
Standard format to store large sequence alignment data
oBAM: compressed binary version
Standard/common data formats
o
RNA-sequencing
Transcriptome profiling using deep sequencing technologies
Quickly and cheaply
Typical experiment
oIsolate RNA and make cDNA library
oFragment
oSequence using NGS
oAlign short reads with reference genome or transcriptome
oThree types of reads: exonic, junction, polyA end
Genome sequencing and assembly
find more resources at oneclass.com
find more resources at oneclass.com
Document Summary
1-1. 5 hours, but will have the whole 3 hours to complete. There will be 1 question on genome assembly on the final exam, but the exercise will be ungraded. Need to know long reads versus short reads, sanger sequencing versus next generation sequencing. As for coding, she will ask what something means, but we will not write code off the top of our head. Unix shell lets you talk with the machine and send files. Perl = practical extraction and reporting language: quick to program something functional for day to day work, high pattern finding capacity, has a lot of mark up (more annotations, more tags) o. Shebang line tells the computer that this is perl code and where to find perl (the interpreter) Life is complex, so we want to find out more information. Transcription: there are many transcripts coming out from one gene -> this can tell us how much proteins to expect.
