Biol375 2018 - Revision history

imported>Weigang: /* Part 4. Mechanisms of molecular evolution */

2018-12-11T17:51:24Z

Part 4. Mechanisms of molecular evolution

← Older revision		Revision as of 17:51, 11 December 2018
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	* 12/3 (M). SNP statistics & gene frequency analysis: In-class exercises.		* 12/3 (M). SNP statistics & gene frequency analysis: In-class exercises.
	* 12/6 (TH) Genetic Drift (pages 47-49). Lecture slides: [[File:Part-4-evol-mechanism-2018.pdf\|thumbnail]]		* 12/6 (TH) Genetic Drift (pages 47-49). Lecture slides: [[File:Part-4-evol-mechanism-2018.pdf\|thumbnail]]
	* 12/10 (M). (Last Lecture) Review & Course evaluations. In-~~class exercise~~.		* 12/10 (M). (Last Lecture) Review & Course evaluations. Final review slides: [[File:Final-review-2018.pdf\|thumbnail]]
	** '''Submit your Teacher's Evaluation''', using either:		** '''Submit your Teacher's Evaluation''', using either:
	** Personal computer at [http://www.hunter.cuny.edu/te www.hunter.cuny.edu/te]; or,		** Personal computer at [http://www.hunter.cuny.edu/te www.hunter.cuny.edu/te]; or,
	** Smartphone at [http://www.hunter.cuny.edu/mobilete www.hunter.cuny.edu/mobilete]		** Smartphone at [http://www.hunter.cuny.edu/mobilete www.hunter.cuny.edu/mobilete]
	* 12/17 (Monday, 4-6pm) '''Comprehensive Final Exam'''		* 12/17 (Monday, 4-6pm) '''Comprehensive Final Exam'''

imported>Weigang: /* Part 4. Mechanisms of molecular evolution */

2018-12-08T02:23:59Z

Part 4. Mechanisms of molecular evolution

← Older revision		Revision as of 02:23, 8 December 2018
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	* 12/3 (M). SNP statistics & gene frequency analysis: In-class exercises.		* 12/3 (M). SNP statistics & gene frequency analysis: In-class exercises.
	* 12/6 (TH) Genetic Drift (pages 47-49). In-~~class exercise: Simulation using R~~		* 12/6 (TH) Genetic Drift (pages 47-49). Lecture slides: [[File:Part-4-evol-mechanism-2018.pdf\|thumbnail]]
	* 12/10 (M). (Last Lecture) Review & Course evaluations. In-class exercise.		* 12/10 (M). (Last Lecture) Review & Course evaluations. In-class exercise.
	** '''Submit your Teacher's Evaluation''', using either:		** '''Submit your Teacher's Evaluation''', using either:

imported>Weigang: /* Part 4. Mechanisms of molecular evolution */

2018-12-06T21:17:08Z

Part 4. Mechanisms of molecular evolution

← Older revision		Revision as of 21:17, 6 December 2018
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	* 12/3 (M). SNP statistics & gene frequency analysis: In-class exercises.		* 12/3 (M). SNP statistics & gene frequency analysis: In-class exercises.
	* 12/6 (TH) Genetic Drift (pages 47-49). In-class exercise: Simulation using R		* 12/6 (TH) Genetic Drift (pages 47-49). In-class exercise: Simulation using R
	* 12/11 (M). (Last Lecture) Review & Course evaluations. In-class exercise.		* 12/10 (M). (Last Lecture) Review & Course evaluations. In-class exercise.
	** '''Submit your Teacher's Evaluation''', using either:		** '''Submit your Teacher's Evaluation''', using either:
	** Personal computer at [http://www.hunter.cuny.edu/te www.hunter.cuny.edu/te]; or,		** Personal computer at [http://www.hunter.cuny.edu/te www.hunter.cuny.edu/te]; or,
	** Smartphone at [http://www.hunter.cuny.edu/mobilete www.hunter.cuny.edu/mobilete]		** Smartphone at [http://www.hunter.cuny.edu/mobilete www.hunter.cuny.edu/mobilete]
	* 12/17 (Monday, 4-6pm) '''Comprehensive Final Exam'''		* 12/17 (Monday, 4-6pm) '''Comprehensive Final Exam'''

imported>Weigang: bootstrap

2018-11-29T22:22:10Z

bootstrap

← Older revision		Revision as of 22:22, 29 November 2018
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	## Compare the two trees and explain the differences in these two methods: Which one uses full sequence information and why?		## Compare the two trees and explain the differences in these two methods: Which one uses full sequence information and why?
	# Bootstrap analysis		# Bootstrap analysis
	## aln.fas <- read.dna("anoles-aligned,~~txt~~")		## aln.fas <- read.dna("anoles-aligned.txt", format ="fasta")
	## Create a function for re-rooted distance tree: tree.fun = function(x) root(nj(dist.dna(x)), outgroup = c("Leiocephalus_barahonensis"), resolve.root = T)		## Create a function for re-rooted distance tree: tree.fun = function(x) root(nj(dist.dna(x)), outgroup = c("Leiocephalus_barahonensis"), resolve.root = T)
	## Calculate a tree: tr = tree.fun(aln.fas)		## Calculate a tree: tr = tree.fun(aln.fas)

imported>Weigang: bootstrap correction

2018-11-29T22:13:23Z

bootstrap correction

← Older revision		Revision as of 22:13, 29 November 2018
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	## Compare the two trees and explain the differences in these two methods: Which one uses full sequence information and why?		## Compare the two trees and explain the differences in these two methods: Which one uses full sequence information and why?
	# Bootstrap analysis		# Bootstrap analysis
			## aln.fas <- read.dna("anoles-aligned,txt")
	## Create a function for re-rooted distance tree: tree.fun = function(x) root(nj(dist.dna(x)), outgroup = c("Leiocephalus_barahonensis"), resolve.root = T)		## Create a function for re-rooted distance tree: tree.fun = function(x) root(nj(dist.dna(x)), outgroup = c("Leiocephalus_barahonensis"), resolve.root = T)
	## Calculate a tree: tr = tree.fun(mt)		## Calculate a tree: tr = tree.fun(aln.fas)
	## Perform bootstrap for 100 pseudo-replicates: boot.trees = boot.phylo(tr, mt, f, B=100, rooted =T)		## Perform bootstrap for 100 pseudo-replicates: boot.trees = boot.phylo(tr, aln.fas, tree.fun, B=100, rooted =T)
	## Plot tree: plot(tr, no.margin = T)		## Plot tree: plot(tr, no.margin = T)
	## Add bootstrap values as node labels: nodelabels(boot.trees, bg= "white")		## Add bootstrap values as node labels: nodelabels(boot.trees, bg= "white")

imported>Weigang: /* Part 4. Mechanisms of molecular evolution */

2018-11-29T22:09:15Z

Part 4. Mechanisms of molecular evolution

← Older revision		Revision as of 22:09, 29 November 2018
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	## Compare the two trees and explain the differences in these two methods: Which one uses full sequence information and why?		## Compare the two trees and explain the differences in these two methods: Which one uses full sequence information and why?
	# Bootstrap analysis		# Bootstrap analysis
	## Create a function for re-rooted distance tree: tree.fun = function(x) root(nj(dist.dna(x)), outgroup = c("~~lemur~~"), resolve.root = T)		## Create a function for re-rooted distance tree: tree.fun = function(x) root(nj(dist.dna(x)), outgroup = c("Leiocephalus_barahonensis"), resolve.root = T)
	## Calculate a tree: tr = tree.fun(mt)		## Calculate a tree: tr = tree.fun(mt)
	## Perform bootstrap for 100 pseudo-replicates: boot.trees = boot.phylo(tr, mt, f, B=100, rooted =T)		## Perform bootstrap for 100 pseudo-replicates: boot.trees = boot.phylo(tr, mt, f, B=100, rooted =T)

imported>Weigang: /* Part 4. Mechanisms of molecular evolution */

2018-11-27T22:29:08Z

Part 4. Mechanisms of molecular evolution

← Older revision		Revision as of 22:29, 27 November 2018
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	===Part 4. Mechanisms of molecular evolution===		===Part 4. Mechanisms of molecular evolution===
	* 11/19 (M). Mechanism of molecular evolution: Overview (pages 35-38)~~; In~~-~~class exercise: SNP statistics~~		* 11/19 (M). Mechanism of molecular evolution: Overview (pages 35-38) & Rates of nucleotide substitutions (pages 111-125).
	* 11/26 (M). ~~Rates~~ of ~~nucleotide substitutions~~ (~~pages 111~~-~~125~~). ~~Neutral Theory & Molecular Clock~~ (~~pages 58~~-~~59; 72-74)~~		* 11/26 (M). Ka/Ks test of natural selection (pg 116-124). In-class exercise
			* 11/29 (TH). In-class computer exercise:
	{\| class="wikitable sortable mw-collapsible"		{\| class="wikitable sortable mw-collapsible"
	\|- style="background-color:lightsteelblue;"		\|- style="background-color:lightsteelblue;"
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	## Explain (1) Does bootstrap test for tree precision or tree accuracy? (2) What does a bootstrap value of 80% mean?		## Explain (1) Does bootstrap test for tree precision or tree accuracy? (2) What does a bootstrap value of 80% mean?
	\|}		\|}
	* 11/29 (~~TH). Ka/Ks test of natural selection (pg 116-124~~). In-class ~~exercise~~		* 12/3 (M). SNP statistics & gene frequency analysis: In-class exercises.
	* 12/3 (M). Genetic Drift (pages 47-49). In-class exercise: Simulation using R		* 12/6 (TH) Genetic Drift (pages 47-49). In-class exercise: Simulation using R
	* 12/6 (TH) Gene frequency analysis
	* 12/11 (M). (Last Lecture) Review & Course evaluations. In-class exercise.		* 12/11 (M). (Last Lecture) Review & Course evaluations. In-class exercise.
	** '''Submit your Teacher's Evaluation''', using either:		** '''Submit your Teacher's Evaluation''', using either:

imported>Weigang: /* Part 4. Mechanisms of molecular evolution */

2018-11-27T17:55:52Z

Part 4. Mechanisms of molecular evolution

← Older revision		Revision as of 17:55, 27 November 2018
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	{\| class="wikitable sortable mw-collapsible"		{\| class="wikitable sortable mw-collapsible"
	\|- style="background-color:lightsteelblue;"		\|- style="background-color:lightsteelblue;"
	! Final project (20 pts). Due: 12/3)		! Final project (20 pts). Due: 12/6, Thursday)
	\|- style="background-color:white;"		\|- style="background-color:white;"
	\|		\|
	# Calculate genetic distances		# Calculate genetic distances
	## Download or Copy/Paste [http://media.hhmi.org/biointeractive/activities/lizard/Anolis-DNA-sequences.txt the lizard DNA sequences] to your own computer and save the file as "~~lizard~~.txt"		## Download or Copy/Paste [http://media.hhmi.org/biointeractive/activities/lizard/Anolis-DNA-sequences.txt the lizard DNA sequences] to your own computer and save the file as "anoles.txt"
	## Align the DNA sequences [http://www.phylogeny.fr/one_task.cgi?task_type=muscle using this website] and save the aligned DNA file ("Output->Alignment in Fasta format") as "~~lizard~~-aligned.txt" (No need to print or submit the above two DNA sequence files; save them ~~for next week's assignment~~)		## Align the DNA sequences [http://www.phylogeny.fr/one_task.cgi?task_type=muscle using this website] and save the aligned DNA file ("Output->Alignment in Fasta format") as "anoles-aligned.txt" (No need to print or submit the above two DNA sequence files; save them in a folder)
	## Load library: library(ape)		## Load library: library(ape)
	## Read alignment: mt = read.FASTA("~~Mt_primate~~.txt")		## Read alignment: mt = read.FASTA("anoles-aligned.txt")
	## Calculate raw distance: mt.raw = dist.dna(mt, model = "raw")		## Calculate raw distance: mt.raw = dist.dna(mt, model = "raw")
	## Apply Juke-Cantor (one-parameter model) correction: mt.jc = dist.dna(mt, model = "JC")		## Apply Juke-Cantor (one-parameter model) correction: mt.jc = dist.dna(mt, model = "JC")
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	## Use the graph to explain (1) Why it is necessary to correct for raw distances when comparing sequences from distantly related species; (2) What is the key difference between the K80 and JC models		## Use the graph to explain (1) Why it is necessary to correct for raw distances when comparing sequences from distantly related species; (2) What is the key difference between the K80 and JC models
	# Comparison of distance and parsimony trees (review previous assignments for detailed R-Studio instructions)		# Comparison of distance and parsimony trees (review previous assignments for detailed R-Studio instructions)
	## In R studio, load the "ape" and "phangnorm" libraries		## In R studio, install & load the "ape" and "phangnorm" libraries
	~~## Read the "Mt_primate.txt" file, save as "aln"~~		### Obtain a neighbor-joining tree using K80 model: tree.nj = NJ(mt.k80)
	~~## Obtain a distance tree:~~
	~~### Calculate K80 distance matrix, save as "mt.dist"~~
	### Obtain a neighbor-joining tree: tree.nj = NJ(mt.~~dist~~)
	### Plot a midpoint rooted tree: plot(midpoint(tree.nj))		### Plot a midpoint rooted tree: plot(midpoint(tree.nj))
	### Add a scale bar: add.scale.bar()		### Add a scale bar: add.scale.bar()
	### Print tree and answer this question: what does the distance represent? What is the unit?		### Print tree and answer this question: what does the distance represent? What is the unit?
	## Obtain a maximum parsimony tree		## Obtain a maximum parsimony tree
	### Convert object to a different class: aln.phy = as.phyDat(~~aln~~)		### Convert object to a different class: aln.phy = as.phyDat(mt)
	### Search maximum parsimony tree.mp = optim.parsimony(tree.nj, aln.phy)		### Search maximum parsimony tree.mp = optim.parsimony(tree.nj, aln.phy)
	### Get tree distance: tree.mp = acctran(tree.mp, aln.phy)		### Get tree distance: tree.mp = acctran(tree.mp, aln.phy)
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	## Compare the two trees and explain the differences in these two methods: Which one uses full sequence information and why?		## Compare the two trees and explain the differences in these two methods: Which one uses full sequence information and why?
	# Bootstrap analysis		# Bootstrap analysis
	~~## Read alignment: aln.fas = read.dna("Mt_primate.txt", format = "fasta")~~		## Create a function for re-rooted distance tree: tree.fun = function(x) root(nj(dist.dna(x)), outgroup = c("lemur"), resolve.root = T)
	## Create a function for re-rooted distance tree: f = function(x) root(nj(dist.dna(x)), outgroup = c("lemur~~", "tarsier~~"), resolve.root = T)		## Calculate a tree: tr = tree.fun(mt)
	## Calculate a tree: tr = f(~~aln.fas~~)		## Perform bootstrap for 100 pseudo-replicates: boot.trees = boot.phylo(tr, mt, f, B=100, rooted =T)
	## Perform bootstrap for 100 pseudo-replicates: boot.trees = boot.phylo(tr, ~~aln.fas~~, f, B=100, rooted =T)
	## Plot tree: plot(tr, no.margin = T)		## Plot tree: plot(tr, no.margin = T)
	## Add bootstrap values as node labels: nodelabels(boot.trees, bg= "white")		## Add bootstrap values as node labels: nodelabels(boot.trees, bg= "white")

imported>Weigang: /* Part 4. Mechanisms of molecular evolution (Chapter 2) */

2018-11-27T17:42:36Z

Part 4. Mechanisms of molecular evolution (Chapter 2)

← Older revision		Revision as of 17:42, 27 November 2018
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	* 11/15 (TH). '''Midterm Exam 3'''		* 11/15 (TH). '''Midterm Exam 3'''

	===Part 4. Mechanisms of molecular evolution ~~(Chapter 2)~~ ===		===Part 4. Mechanisms of molecular evolution===
	* 11/19 (M). Mechanism of molecular evolution: Overview (pages 35-38); In-class exercise: SNP statistics		* 11/19 (M). Mechanism of molecular evolution: Overview (pages 35-38); In-class exercise: SNP statistics
	* 11/26 (M). Rates of nucleotide substitutions (pages 111-125). Neutral Theory & Molecular Clock (pages 58-59; 72-74)		* 11/26 (M). Rates of nucleotide substitutions (pages 111-125). Neutral Theory & Molecular Clock (pages 58-59; 72-74)

imported>Weigang: /* Part 4. Mechanisms of molecular evolution (Chapter 2) */

2018-11-20T23:16:32Z

Part 4. Mechanisms of molecular evolution (Chapter 2)

← Older revision		Revision as of 23:16, 20 November 2018
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	{\| class="wikitable sortable mw-collapsible"		{\| class="wikitable sortable mw-collapsible"
	\|- style="background-color:lightsteelblue;"		\|- style="background-color:lightsteelblue;"
	! Final project (10 pts). Due: 12/3)		! Final project (20 pts). Due: 12/3)
	\|- style="background-color:white;"		\|- style="background-color:white;"
	\|		\|