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Add method for affiliation analysis #35

Merged
merged 19 commits into from
Mar 13, 2020
Merged

Add method for affiliation analysis #35

merged 19 commits into from
Mar 13, 2020

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trangdata
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@cgreene
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cgreene commented Mar 9, 2020

One of the things we've gotten critiqued over is grouping countries. I don't think the critique undercuts the primary message of the paper, but I think we might get a lot of mileage out of a table that breaks down results by country. This was infeasible with names, but should be feasible with affiliations.

I'm imagining a table with the product of literature fraction * number of honorees compared against the actual number of honorees from that country.

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dhimmel commented Mar 9, 2020

I think we might get a lot of mileage out of a table that breaks down results by country. This was infeasible with names, but should be feasible with affiliations.

Yes, I think a country enrichment / depletion analysis would be really helpful and more fine-grained then regions.

However, I it would be best to proceed with this PR as is, and decide to replace the region-affiliation analyses later.

I'll review line-by-line now.

content/20.results.md Outdated Show resolved Hide resolved
Along with the corresponding author names, we collected their affiliations recorded in each publication for this analysis.
During the honoree curation process, if an honoree was listed with their affiliation at the time, we recorded this affiliation for analysis.
Because we could not find affiliations for the 1997 and 1998 RECOMB keynote speakers' listed for these years, they were left blank.
We used the [standard world geographical mapping](https://raw.githubusercontent.com/greenelab/iscb-diversity/b41b8fad157d0b878a2476cec998aba0643742bf/figs/2020-01-31_natural-earth-world-map.png) from the R package `rnaturalearth` to group the countries of affiliation in seven different regions: North America, Europe & Central Asia, East Asia & Pacific, Latin America & Caribbean, South Asia, Middle East & North Africa and Sub-Saharan Africa.
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I can't find anything online for "standard world geographical mapping". Tracking the data back its from the region_wb column of data/countries/world-map.tsv. Sounds like this is from Natural Earth. I'll look for some documentation of region_wb that we can point to... basically who makes it and via what criteria / what region_wb is defined as.

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I agree that we need to source the mapping.

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I had a few suggested changes. I am not confident in the wording of all of them, so please take a careful look :)

content/10.methods.md Show resolved Hide resolved
Along with the corresponding author names, we collected their affiliations recorded in each publication for this analysis.
During the honoree curation process, if an honoree was listed with their affiliation at the time, we recorded this affiliation for analysis.
Because we could not find affiliations for the 1997 and 1998 RECOMB keynote speakers' listed for these years, they were left blank.
We used the [standard world geographical mapping](https://raw.githubusercontent.com/greenelab/iscb-diversity/b41b8fad157d0b878a2476cec998aba0643742bf/figs/2020-01-31_natural-earth-world-map.png) from the R package `rnaturalearth` to group the countries of affiliation in seven different regions: North America, Europe & Central Asia, East Asia & Pacific, Latin America & Caribbean, South Asia, Middle East & North Africa and Sub-Saharan Africa.
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I agree that we need to source the mapping.

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trangdata and others added 11 commits March 10, 2020 13:55
Co-Authored-By: Casey Greene <[email protected]>
Co-Authored-By: Casey Greene <[email protected]>
Co-Authored-By: Casey Greene <[email protected]>
Co-Authored-By: Casey Greene <[email protected]>
Co-Authored-By: Casey Greene <[email protected]>
Co-Authored-By: Casey Greene <[email protected]>
Co-Authored-By: Casey Greene <[email protected]>
Co-Authored-By: Casey Greene <[email protected]>
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trangdata commented Mar 10, 2020

One of the things we've gotten critiqued over is grouping countries. I don't think the critique undercuts the primary message of the paper, but I think we might get a lot of mileage out of a table that breaks down results by country. This was infeasible with names, but should be feasible with affiliations.

Affiliation analysis html now updated by this commit.

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Now that the country-level analysis is in much better shape, should we replace the group level analysis with it? @cgreene @dhimmel

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cgreene commented Mar 11, 2020

I think that would be a good idea. I feel like the country level analysis addresses a lot of the concerns that have been raised by Iddo in #27 and others.

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trangdata commented Mar 11, 2020

OK I'm happy to close this issue and open a new one if that's easiest for everyone! Or we can merge to keep part of the Methods section and I'll make another PR to change what we want to focus on in the Results.

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cgreene commented Mar 12, 2020

Well, the methods changes would apply regardless except for the bit about grouping. What do you think about keeping those changes and dropping the changes to the results. The results changes with a country-level analysis could be added by a separate pull request. We could then go ahead and merge this if we wanted to (I'm more comfortable merging methods before results than vice versa) or hold on until they're both ready and merge about the same time.

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Looks good!

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Co-Authored-By: Casey Greene <[email protected]>
@trangdata trangdata changed the title Add affiliation analysis Add method for affiliation analysis Mar 13, 2020
@trangdata trangdata merged commit 47bd038 into master Mar 13, 2020
@trangdata trangdata deleted the add-affiliation branch March 13, 2020 20:13
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3 participants