Post date: May 24, 2017 6:34:51 PM
24v17. I made a new morphoj project with the following updates.
Megan remeasured four wings since they stood out as outliers yesterday: CP12-77, HNV07-08, MM07-208, SHC11-15.
>Megan is going to measure more FCR and CSP wings for which I had taken pictures for other projects in 2012. She'll be done with these tomorrow, probably.
>I also gave her three new populations to add to the dataset before we publish: SWM, CAV, LAE. She'll have to take pictures and measure them. She'll be done by July.
In coord-raw-nowing-no0-subgroup.csv:
-I added Megan's remeasured wings.
-I replaced 0's with -9999's.
-I added a subgroup identifier to the end of the name. For the key, see mapping-n-23may17.xlsx
-then I redid in morphoj: classifiers, procrustes, covariance matrix, wireframe, PCA.
-subgroups overlap quite a bit, with ricei sort of on one end, and melissa on the other (sort of)
Next steps:
-By population, do a regression with size, sex, and size by sex, for size and coord data separately.
-Then redo PCA for fun with transformed residuals.
-Then explore modularity hypothesis. First with all individuals in the dataset. Start with positions since this is easiest in morphoj.
Do I take the vein landmarks out for this? All landmarks have to be put in a module.
Playing with modularity with the raw data, no residuals
Reminder: For morphometric studies of modularity, a configuration of landmarks can be subdivided into subsets corresponding to the hypothesized modules. If the partition corresponds to the true boundary between modules (blue line in the diagram), covariation between subsets is expected to be weak because it reflects only the weak between-module covariation. In contrast, if the partition into subsets cuts across modules (red line), covariation between subsets is expected to be stronger, because the subsets are linked by the strong within-module integration. If the hypothesis of modularity is true, the covariation between subsets of landmarks corresponding to the hypothesis should be lower than for different subdivisions of the landmarks (Klingenberg 2009). This reasoning provides an approach for evaluating a-priori hypotheses about modularity by comparing the degree of covariation for the hypothesis to the range of covariation for alternative partitions. If the hypothesized subsets of landmarks correspond to the true modules, a lower covariation is expected for this partition than for any other subdivision of landmarks. Low covariation, by itself, does not imply modularity, but it is a prediction of the modularity hypothesis. Therefore, if covariation between the subsets for the hypothesis of modularity is not weaker than for most or all of the alternative partitions, the hypothesis of modularity can be rejected (Klingenberg 2009).
Settings: contiguous and non-contiguous partitions were considered. only a sample of random partitions were analyzed: 10000
1. Hypothesis 1: black spots vs aurorae vs veins
Multi-set RV coefficient: 0.343458
Modules with minimal RV: no super clear pattern
2. Hypothesis 2: anteriorVSposterior
RV coefficient: 0.566877
Modules with minimal RV: 3/4/16/17/1122/23/24/26/ vs. everything else
3. Hypothesis 3: within-veins
Multi-set RV coefficient: 0.313599
Modules with minimal RV: no super clear pattern
4. Hypothesis 4: proximal-distal
module 1: 7,8,9,24,25,26
module 2: 10-17
module 3: 1-6, 18-23
Multi-set RV coefficient: 0.274867
Modules with minimal RV: this is the minimum covariation! cool. Same as Klingenberg 2009 with Drosophila.
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Megan's new FCR measurements came in, so now we have 19 FCR wings. I've included them in coord-raw-nowing-noO-subgroup. I started yet another morphoj project: 24v17-all. NOTE: the mod_meas and raw-meas folder no longer have all wing files now, as I've been manually adding the new wings as they've come in today.
I exported centroid size and procrustes coordinates for everyone. They are together in a file called coord-centroidsize-procrustes. Use this file for the regression. I might need to add a population column to this spreadsheet.
The size-24v17.csv has updated raw size data for the regression for wing size vs. element size. Just like the coord file, NA = -9999 and the names include a subgroup classifier. I might need to add a population column to this spreadsheet.