In the past, I have included the data from my papers in supplementaries but I am moving towards sharing via online repositories. I will link to these here. If you find them useful - and more importantly if you identify errors - I would appreciate it if you could let me know using the email ID on the contact page.
2) Data on phytoplankton temperature traits, and growth rates at different temperatures (updated Jan 29th, 2016).
I gathered >7000 published measurements of the population growth rates of individual phytoplankton species at different temperatures, and used these to estimate important traits (such as the optimum temperature for growth) that tell us how ocean and lake temperatures influence phytoplankton. I include both the original growth rates and the estimated traits (and associated metadata) in this dataset. An explanation of the dataset is included inside the attached .zip file. For more details about it, please look at the methods in Thomas et al. (2012) and Thomas et al. (2016), as well as their supplementaries. If you do use this dataset for a publication, I'd appreciate it if you would cite these papers as the data sources.
I do not actively update this dataset but my collaborator Colin Kremer has been building an updated version.
Dataset
1) Code to clean and cluster flow cytometry (FCM) and scanning flow cytometry (SFCM) datasets, along with example dataset (updated August 30th, 2017)
FCM and SFCM are powerful tools to track the dynamics of microbial communities in the lab and field. However, for large, complex datasets, few tools are available to ensure rapid, repeatable analyses. While working with such a dataset in Switzerland, I developed a protocol to clean (i.e. remove signals that are not from live cells) and cluster (i.e. identify subgroups) SFCM data, as well as estimate the biovolumes of individual cells and colonies. The method has been published in PLoS one, and the code and an example dataset are available through Zenodo and Github:
Dataset (DOI: 10.5281/zenodo.977772)
Code (DOI: 10.5281/zenodo.999747)
Though this worked example is based on data from the Cytobuoy, it may be adapted for use with any FCM or SFCM data.
I gathered >7000 published measurements of the population growth rates of individual phytoplankton species at different temperatures, and used these to estimate important traits (such as the optimum temperature for growth) that tell us how ocean and lake temperatures influence phytoplankton. I include both the original growth rates and the estimated traits (and associated metadata) in this dataset. An explanation of the dataset is included inside the attached .zip file. For more details about it, please look at the methods in Thomas et al. (2012) and Thomas et al. (2016), as well as their supplementaries. If you do use this dataset for a publication, I'd appreciate it if you would cite these papers as the data sources.
I do not actively update this dataset but my collaborator Colin Kremer has been building an updated version.
Dataset
1) Code to clean and cluster flow cytometry (FCM) and scanning flow cytometry (SFCM) datasets, along with example dataset (updated August 30th, 2017)
FCM and SFCM are powerful tools to track the dynamics of microbial communities in the lab and field. However, for large, complex datasets, few tools are available to ensure rapid, repeatable analyses. While working with such a dataset in Switzerland, I developed a protocol to clean (i.e. remove signals that are not from live cells) and cluster (i.e. identify subgroups) SFCM data, as well as estimate the biovolumes of individual cells and colonies. The method has been published in PLoS one, and the code and an example dataset are available through Zenodo and Github:
Dataset (DOI: 10.5281/zenodo.977772)
Code (DOI: 10.5281/zenodo.999747)
Though this worked example is based on data from the Cytobuoy, it may be adapted for use with any FCM or SFCM data.
