Details
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Type:
Task
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Status: Closed (View Workflow)
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Priority:
Major
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Resolution: Done
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Affects Version/s: None
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Fix Version/s: None
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Labels:None
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Story Points:2
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Sprint:Fall 2 2023 Sep 17, Fall 3 2023 Oct 2
Description
We observed from previous work that VF36 and F3H are very similar with respect to gene expression patterns. To understand how the are mutant differs from wild-type, we will focus on comparing the are mutant to the VF36 cultivar.
Goal: Find and interpret how gene expression in are differs from gene expression in VF36
Rationale: Based on past PCA and MDS plot analysis, we hypothesize there will many genes with expression differences between ARE and VF36. And yet, as far as we know, ARE is nothing but VF36 with a single point mutation in the F3H gene. Why so many differences in expression?
Strategy:
Create Markdown that perform differential analysis comparing are to VF36 within the control 28 degree temperature and under one time.
Attachments
Activity
| Field | Original Value | New Value |
|---|---|---|
| Assignee | Ann Loraine [ aloraine ] |
| Epic Link |
|
| Summary | Differential Expression Analysis: VF36 versus ARE | Analyze DE genes for VF36 vs. ARE |
| Summary | Analyze DE genes for VF36 vs. ARE | Analyze and compare DE genes for VF36 and ARE |
| Sprint | Summer 1 2023 May 15 [ 170 ] | Summer 2 2023 May 29 [ 171 ] |
| Story Points | 1 | 4 |
| Description | To see if we can unravel if there are genetic differences beyond the singe point mutation that we expect in ARE. |
To see if we can unravel if there are genetic differences beyond the singe point mutation that we expect in ARE.
Create a new Markdown that compares gene expression between VF36 and ARE. Which genes if any are differentially expressed between VF36 control and ARE control samples? Create a new Markdown CompareVF36andARE.Rmd |
| Comment |
[ For the life of me, can't seem to assign this to the proper EPIC !!!!!
There is not option. That needs to be resolved! R ] |
| Summary | Analyze and compare DE genes for VF36 and ARE | Analyze and compare DE genes between VF36 and ARE |
| Summary | Analyze and compare DE genes between VF36 and ARE | Analyze and compare gene expression between F36 and ARE controls |
| Summary | Analyze and compare gene expression between F36 and ARE controls | Analyze and compare gene expression between VF36 and ARE controls |
| Description |
To see if we can unravel if there are genetic differences beyond the singe point mutation that we expect in ARE.
Create a new Markdown that compares gene expression between VF36 and ARE. Which genes if any are differentially expressed between VF36 control and ARE control samples? Create a new Markdown CompareVF36andARE.Rmd |
To see if we can unravel if there are genetic differences beyond the singe point mutation that we expect in ARE.
Create a new Markdown that compares gene expression between VF36 and ARE. Which genes if any are differentially expressed between VF36 control and ARE control samples? Create a new Markdown CompareVF36andARE.Rmd Based on the MDS plot clustering patterns, we expect there will many genes with expression differences between ARE and VF36. And yet, as far as we know, ARE is nothing but VF36 with a single point mutation in the F3H gene! WTF? |
| Description |
To see if we can unravel if there are genetic differences beyond the singe point mutation that we expect in ARE.
Create a new Markdown that compares gene expression between VF36 and ARE. Which genes if any are differentially expressed between VF36 control and ARE control samples? Create a new Markdown CompareVF36andARE.Rmd Based on the MDS plot clustering patterns, we expect there will many genes with expression differences between ARE and VF36. And yet, as far as we know, ARE is nothing but VF36 with a single point mutation in the F3H gene! WTF? |
To see if we can unravel if there are genetic differences beyond the singe point mutation that we expect in ARE.
Create a new Markdown that compares gene expression between VF36 and ARE. Which genes if any are differentially expressed between VF36 control and ARE control samples? Create a new Markdown CompareVF36andARE.Rmd Based on the MDS plot clustering patterns, we expect there will many genes with expression differences between ARE and VF36. And yet, as far as we know, ARE is nothing but VF36 with a single point mutation in the F3H gene! WTF? One possibility is that mucking around the flavonoid biosynthesis pathway causes genome-wide differences in expression for lots and lots of genes due to some as-yet undeterimed role for flavonoids in maintaining core metabolism. |
| Sprint | Summer 2 2023 May 29 [ 171 ] |
| Rank | Ranked higher |
| Description |
To see if we can unravel if there are genetic differences beyond the singe point mutation that we expect in ARE.
Create a new Markdown that compares gene expression between VF36 and ARE. Which genes if any are differentially expressed between VF36 control and ARE control samples? Create a new Markdown CompareVF36andARE.Rmd Based on the MDS plot clustering patterns, we expect there will many genes with expression differences between ARE and VF36. And yet, as far as we know, ARE is nothing but VF36 with a single point mutation in the F3H gene! WTF? One possibility is that mucking around the flavonoid biosynthesis pathway causes genome-wide differences in expression for lots and lots of genes due to some as-yet undeterimed role for flavonoids in maintaining core metabolism. |
To see if we can unravel if there are genetic differences beyond the single point mutation that we expect in ARE.
Create a new Markdown that compares gene expression between VF36 and ARE. Which genes if any are differentially expressed between VF36 control and ARE control samples? Create a new Markdown CompareVF36andARE.Rmd Based on clustering patterns, we expect there will many genes with expression differences between ARE and VF36. And yet, as far as we know, ARE is nothing but VF36 with a single point mutation in the F3H gene. Why so many differences in expression? |
| Story Points | 4 | 2 |
| Description |
To see if we can unravel if there are genetic differences beyond the single point mutation that we expect in ARE.
Create a new Markdown that compares gene expression between VF36 and ARE. Which genes if any are differentially expressed between VF36 control and ARE control samples? Create a new Markdown CompareVF36andARE.Rmd Based on clustering patterns, we expect there will many genes with expression differences between ARE and VF36. And yet, as far as we know, ARE is nothing but VF36 with a single point mutation in the F3H gene. Why so many differences in expression? |
To see if we can unravel if there are genetic differences beyond the single point mutation that we expect in ARE.
Create a new Markdown that compares gene expression between VF36 and _are_ same-temperature samples. Ann's suggestion: Combine all the time points within a temperature to capture variation over time and age of pollen tubes. Genes that respond to unknown background variables will likely vary a lot within a genotype+temperature combination, making it impossible to tell if genotype makes a difference. That's cool. We are not interesting in those genes here. What we care about are: genes that are CONSISTENTLY differentially expressed between VF36 and the _are_ mutant. We hypothesize that genes involved in flavonoid biosynthesis are most likely to be different between the _are_ mutant and VF36 genotypes. Create a new Markdown CompareVF36andARE.Rmd Based on clustering patterns, we expect there will many genes with expression differences between ARE and VF36. And yet, as far as we know, ARE is nothing but VF36 with a single point mutation in the F3H gene. Why so many differences in expression? |
| Summary | Analyze and compare gene expression between VF36 and ARE controls | Enable analyzing and comparing gene expression between VF36 and ARE controls |
| Description |
To see if we can unravel if there are genetic differences beyond the single point mutation that we expect in ARE.
Create a new Markdown that compares gene expression between VF36 and _are_ same-temperature samples. Ann's suggestion: Combine all the time points within a temperature to capture variation over time and age of pollen tubes. Genes that respond to unknown background variables will likely vary a lot within a genotype+temperature combination, making it impossible to tell if genotype makes a difference. That's cool. We are not interesting in those genes here. What we care about are: genes that are CONSISTENTLY differentially expressed between VF36 and the _are_ mutant. We hypothesize that genes involved in flavonoid biosynthesis are most likely to be different between the _are_ mutant and VF36 genotypes. Create a new Markdown CompareVF36andARE.Rmd Based on clustering patterns, we expect there will many genes with expression differences between ARE and VF36. And yet, as far as we know, ARE is nothing but VF36 with a single point mutation in the F3H gene. Why so many differences in expression? |
To see if we can unravel if there are genetic differences beyond the single point mutation that we expect in ARE.
Make it possible for Muday lab to easily analyze and compare gene expression between VF36 and are genotypes. Create a new Markdown that compares gene expression between VF36 and _are_ same-temperature samples. Ann's suggestion: Combine all the time points within a temperature to capture variation over time and age of pollen tubes. Genes that respond to unknown background variables will likely vary a lot within a genotype+temperature combination, making it impossible to tell if genotype makes a difference. That's cool. We are not interesting in those genes here. What we care about are: genes that are CONSISTENTLY differentially expressed between VF36 and the _are_ mutant. We hypothesize that genes involved in flavonoid biosynthesis are most likely to be different between the _are_ mutant and VF36 genotypes. Create a new Markdown CompareVF36andARE.Rmd Based on clustering patterns, we expect there will many genes with expression differences between ARE and VF36. And yet, as far as we know, ARE is nothing but VF36 with a single point mutation in the F3H gene. Why so many differences in expression? |
| Summary | Enable analyzing and comparing gene expression between VF36 and ARE controls | Enable analyzing and comparing gene expression between VF36 and are genotypes |
| Summary | Enable analyzing and comparing gene expression between VF36 and are genotypes | Enable analyzing and comparing gene expression between _are_ and VF36 genotypes |
| Summary | Enable analyzing and comparing gene expression between _are_ and VF36 genotypes | Enable analyzing and comparing gene expression between are and VF36 genotypes |
| Description |
To see if we can unravel if there are genetic differences beyond the single point mutation that we expect in ARE.
Make it possible for Muday lab to easily analyze and compare gene expression between VF36 and are genotypes. Create a new Markdown that compares gene expression between VF36 and _are_ same-temperature samples. Ann's suggestion: Combine all the time points within a temperature to capture variation over time and age of pollen tubes. Genes that respond to unknown background variables will likely vary a lot within a genotype+temperature combination, making it impossible to tell if genotype makes a difference. That's cool. We are not interesting in those genes here. What we care about are: genes that are CONSISTENTLY differentially expressed between VF36 and the _are_ mutant. We hypothesize that genes involved in flavonoid biosynthesis are most likely to be different between the _are_ mutant and VF36 genotypes. Create a new Markdown CompareVF36andARE.Rmd Based on clustering patterns, we expect there will many genes with expression differences between ARE and VF36. And yet, as far as we know, ARE is nothing but VF36 with a single point mutation in the F3H gene. Why so many differences in expression? |
To see if we can unravel if there are genetic differences beyond the single point mutation that we expect in ARE.
Make it possible for Muday lab to easily analyze and compare gene expression between VF36 and are genotypes by creating a new Markdown that identifies differentially expressed genes between VF36 and _are_ same-temperature samples. Ann's suggestion: Combine all the time points within a temperature to capture variation over time and age of pollen tubes. Genes that respond to unknown background variables will likely vary a lot within a genotype+temperature combination, making it impossible to tell if genotype makes a difference. That's cool. We are not interesting in those genes here. What we care about are: genes that are CONSISTENTLY differentially expressed between VF36 and the _are_ mutant. We hypothesize that genes involved in flavonoid biosynthesis are most likely to be different between the _are_ mutant and VF36 genotypes. Create a new Markdown CompareVF36andARE.Rmd Based on clustering patterns, we expect there will many genes with expression differences between ARE and VF36. And yet, as far as we know, ARE is nothing but VF36 with a single point mutation in the F3H gene. Why so many differences in expression? |
| Description |
To see if we can unravel if there are genetic differences beyond the single point mutation that we expect in ARE.
Make it possible for Muday lab to easily analyze and compare gene expression between VF36 and are genotypes by creating a new Markdown that identifies differentially expressed genes between VF36 and _are_ same-temperature samples. Ann's suggestion: Combine all the time points within a temperature to capture variation over time and age of pollen tubes. Genes that respond to unknown background variables will likely vary a lot within a genotype+temperature combination, making it impossible to tell if genotype makes a difference. That's cool. We are not interesting in those genes here. What we care about are: genes that are CONSISTENTLY differentially expressed between VF36 and the _are_ mutant. We hypothesize that genes involved in flavonoid biosynthesis are most likely to be different between the _are_ mutant and VF36 genotypes. Create a new Markdown CompareVF36andARE.Rmd Based on clustering patterns, we expect there will many genes with expression differences between ARE and VF36. And yet, as far as we know, ARE is nothing but VF36 with a single point mutation in the F3H gene. Why so many differences in expression? |
To see if we can unravel if there are genetic differences beyond the single point mutation that we expect in ARE.
Make it possible for Muday lab to easily analyze and compare gene expression between VF36 and are genotypes by creating a new Markdown that identifies differentially expressed genes between VF36 and _are_ same-temperature samples. Ann's suggestion: Combine all the time points within a temperature to capture variation over time and age of pollen tubes. Genes that respond to other variables will likely vary a lot within a genotype+temperature combination. Doing that will let us find any and all genes that are CONSISTENTLY differentially expressed between VF36 and the _are_ mutant, where the genotype distinction matters far more than other variables we tested. Based on past PCA and MDS plot analysis, we hypothesize there will many genes with expression differences between ARE and VF36. And yet, as far as we know, ARE is nothing but VF36 with a single point mutation in the F3H gene. Why so many differences in expression? |
| Summary | Enable analyzing and comparing gene expression between are and VF36 genotypes | Compare gene expression between are and VF36 genotypes |
| Description |
To see if we can unravel if there are genetic differences beyond the single point mutation that we expect in ARE.
Make it possible for Muday lab to easily analyze and compare gene expression between VF36 and are genotypes by creating a new Markdown that identifies differentially expressed genes between VF36 and _are_ same-temperature samples. Ann's suggestion: Combine all the time points within a temperature to capture variation over time and age of pollen tubes. Genes that respond to other variables will likely vary a lot within a genotype+temperature combination. Doing that will let us find any and all genes that are CONSISTENTLY differentially expressed between VF36 and the _are_ mutant, where the genotype distinction matters far more than other variables we tested. Based on past PCA and MDS plot analysis, we hypothesize there will many genes with expression differences between ARE and VF36. And yet, as far as we know, ARE is nothing but VF36 with a single point mutation in the F3H gene. Why so many differences in expression? |
We observed from previous work that VF36 and F3H are very similar with respect to gene expression patterns. To understand how the _are_ mutant differs from wild-type, we will focus on comparing the are mutant to the VF36 cultivar.
Goal: Find and interpret how gene expression in _are_ differs from gene expression in VF36 Rationale: Based on past PCA and MDS plot analysis, we hypothesize there will many genes with expression differences between ARE and VF36. And yet, as far as we know, ARE is nothing but VF36 with a single point mutation in the F3H gene. Why so many differences in expression? Strategy: Create Markdown that perform differential analysis comparing _are_ to VF36 within the control 28 degree temperature and one time point. |
| Description |
We observed from previous work that VF36 and F3H are very similar with respect to gene expression patterns. To understand how the _are_ mutant differs from wild-type, we will focus on comparing the are mutant to the VF36 cultivar.
Goal: Find and interpret how gene expression in _are_ differs from gene expression in VF36 Rationale: Based on past PCA and MDS plot analysis, we hypothesize there will many genes with expression differences between ARE and VF36. And yet, as far as we know, ARE is nothing but VF36 with a single point mutation in the F3H gene. Why so many differences in expression? Strategy: Create Markdown that perform differential analysis comparing _are_ to VF36 within the control 28 degree temperature and one time point. |
We observed from previous work that VF36 and F3H are very similar with respect to gene expression patterns. To understand how the _are_ mutant differs from wild-type, we will focus on comparing the are mutant to the VF36 cultivar.
Goal: Find and interpret how gene expression in _are_ differs from gene expression in VF36 Rationale: Based on past PCA and MDS plot analysis, we hypothesize there will many genes with expression differences between ARE and VF36. And yet, as far as we know, ARE is nothing but VF36 with a single point mutation in the F3H gene. Why so many differences in expression? Strategy: Create Markdown that perform differential analysis comparing _are_ to VF36 within the control 28 degree temperature and under one time. |
| Summary | Compare gene expression between are and VF36 genotypes | Compare control sample gene expression between are and VF36 genotypes |
| Assignee | Ann Loraine [ aloraine ] |
| Sprint | Fall 2 2023 Sep 17 [ 178 ] |
| Status | To-Do [ 10305 ] | In Progress [ 3 ] |
| Status | In Progress [ 3 ] | Needs 1st Level Review [ 10005 ] |
| Status | Needs 1st Level Review [ 10005 ] | First Level Review in Progress [ 10301 ] |
| Status | First Level Review in Progress [ 10301 ] | Needs 1st Level Review [ 10005 ] |
| Status | Needs 1st Level Review [ 10005 ] | First Level Review in Progress [ 10301 ] |
| Status | First Level Review in Progress [ 10301 ] | Ready for Pull Request [ 10304 ] |
| Status | Ready for Pull Request [ 10304 ] | Pull Request Submitted [ 10101 ] |
| Status | Pull Request Submitted [ 10101 ] | Reviewing Pull Request [ 10303 ] |
| Status | Reviewing Pull Request [ 10303 ] | Merged Needs Testing [ 10002 ] |
| Assignee | Ann Loraine [ aloraine ] |
| Sprint | Fall 2 2023 Sep 17 [ 178 ] | Fall 2 2023 Sep 17, Fall 3 2023 Oct 2 [ 178, 179 ] |
| Rank | Ranked higher |
| Comment |
[ *+Design Notes+*
*Question to answer*: Is the treatment effect different across genotypes? *Understanding results of the interaction term*: https://rdrr.io/bioc/DESeq2/man/results.html#:~:text=object)%24tDegreesFreedom%20.-,Value,standard%20error%20of%20the%20log2FoldChange%20. * I discovered that the results term will just return the comparison of the last level of the last variable in the design formula over the first level of this variable. * If you want to see results for a specific comparison you are supposed to use a contrast argument. In other words, the argument contrast can be used to generate results tables for any comparison of interest. It subtracts to see the difference between the two genotypes. Ex: results(dds, contrast=list("genotypeIII.conditionB", "genotypeII.conditionB")) * resultsNames(): shows the names of the columns available as results, usually a combination of the variable name and a level Examples: {panel} genotypeII.conditionB = gives the condition effect for genotype II vs I genotypeIII.conditionB = gives the condition effect for genotype III vs I {panel} Examples in Code: {code:java} ## Example: two conditions, three genotypes # ~~~ Using interaction terms ~~~ dds <- makeExampleDESeqDataSet(n=100,m=18) dds$genotype <- factor(rep(rep(c("I","II","III"),each=3),2)) design(dds) <- ~ genotype + condition + genotype:condition dds <- DESeq(dds) resultsNames(dds) # the condition effect for genotype I (the main effect) results(dds, contrast=c("condition","B","A")) # the condition effect for genotype III. # this is the main effect *plus* the interaction term # (the extra condition effect in genotype III compared to genotype I). results(dds, contrast=list( c("condition_B_vs_A","genotypeIII.conditionB") )) # the interaction term for condition effect in genotype III vs genotype I. # this tests if the condition effect is different in III compared to I results(dds, name="genotypeIII.conditionB") # the interaction term for condition effect in genotype III vs genotype II. # this tests if the condition effect is different in III compared to II results(dds, contrast=list("genotypeIII.conditionB", "genotypeII.conditionB")) ## where the first element of the list is the numerator (so gets treated positively) and the second is the denominator (so gets subtracted), which leaves the effect you're looking for. # Note that a likelihood ratio could be used to test if there are any # differences in the condition effect between the three genotypes. {code} * Output for each contrast would include results columns: baseMean, log2FoldChange, lfcSE, stat, pvalue and padj *Muday Design*: {code:java} ## Run analysis dds <- DESeqDataSetFromMatrix(countData = round(cts), colData = coldata, design = ~genotype + temperature + genotype:temperature) featureData <- data.frame(gene=rownames(cts)) mcols(dds) <- DataFrame(mcols(dds), featureData) dds <- DESeq(dds, minReplicatesForReplace=Inf) keep <- rowSums(counts(dds)) >= 10 dds <- dds[keep,] resultsNames(dds) # View all of the Design and interactions # this tests if the condition effect is different in genotype III compared to I res_V_vs_A <- results(dds, name="genotypeV.temperature34") res_V_vs_A <- res_V_vs_A[order(res_V_vs_A $pvalue),] # Order by pvalue res_V_vs_A # this tests if the condition effect is different in genotype III compared to II res_V_vs_F <- results(dds, contrast=list("genotypeV.temperature34", "genotypeF.temperature34")) res_V_vs_F <- res_V_vs_F[order(res_V_vs_F$pvalue),] # Order by pvalue res_V_vs_F {code} Notes on Muday Results: * res_V_vs_A * res_V_vs_F *Questions to answer*: * Why not just use the interaction term in the design? The interaction term will not have the same meaning as it would if both main effects were included in the model. It actually allows us to make contrasts down the line. * Why use an interaction term instead of grouping the factors? * Are we actually seeing a difference in gene expression across genotypes based on the condition? * What does log2FoldChange mean and represent within the design? This value indicates how much the gene or transcript's expression seems to have changed between the comparison and control groups. ] |
| Assignee | Molly Davis [ molly ] |
| Status | Merged Needs Testing [ 10002 ] | Post-merge Testing In Progress [ 10003 ] |
Testing:
- Markdown: No issues with build or knitting.
- PDF: The pdf is comprehendible and visually has no issues
- Output files: Output files make sense and have no issues
- IGB Images: Images show genes from the SL4 genome and compare A vs. V genotypes
Everything looks great! Moving to done!
| Comment | [ When I compare result files MvW-SL4.txt & MvW-SL5.txt they do not have similar results. Is there a gene name issue occurring between SL4 and SL5 results? or would genome version effect results? ] |
| Resolution | Done [ 10000 ] | |
| Status | Post-merge Testing In Progress [ 10003 ] | Closed [ 6 ] |
| Assignee | Molly Davis [ molly ] | Ann Loraine [ aloraine ] |
Thanks for the above comments [~molly]!
I made a new Markdown that does compares are control samples to VF36 control samples, including time as a variable.
My rationale for including time as a variable was to ensure that the model could take time effects into account when comparing are to VF36 samples. I did not include the treatment samples because we know that temperature has an effect on gene expression, and I did not want to make results harder to interpret by including the treatment as a factor.
Due to our tight time line I committed my changes to the main branch.
For review and/or testing, please examine the following files:
Images (from IGB) confirming the DE observation for two genes:
For this, I used DESeq2. I analyzed SL4 and SL5 genes separately, and saved the results to the ".txt" files above.
I also checked some of the genes using IGB. I visually confirmed that coverage graphs for genes with small log2 fold-changes between are and VF36 looked pretty much the same. Larger fold-changes were more obvious, even when the expression levels were low, e.g., scaled coverage graph peaks of 6 or smaller.