TY  - JOUR
A1  - Rottler, Erwin
A1  - Vormoor, Klaus Josef
A1  - Francke, Till
A1  - Bronstert, Axel
T1  - Hydro Explorer
BT  - an interactive web app to investigate changes in runoff timing and runoff seasonality all over the world
JF  - River research and applications
N2  - Climatic changes and anthropogenic modifications of the river basin or river network have the potential to fundamentally alter river runoff. In the framework of this study, we aim to analyze and present historic changes in runoff timing and runoff seasonality observed at river gauges all over the world. In this regard, we develop the Hydro Explorer, an interactive web app, which enables the investigation of >7,000 daily resolution discharge time series from the Global Runoff Data Centre (GRDC). The interactive nature of the developed web app allows for a quick comparison of gauges, regions, methods, and time frames. We illustrate the available analytical tools by investigating changes in runoff timing and runoff seasonality in the Rhine River Basin. Since we provide the source code of the application, existing analytical approaches can be modified, new methods added, and the tool framework can be re-used to visualize other data sets.
KW  - global runoff database
KW  - interactive web app
KW  - R Shiny
KW  - runoff
KW  - seasonality
KW  - runoff timing
Y1  - 2021
U6  - https://doi.org/10.1002/rra.3772
SN  - 1535-1459
SN  - 1535-1467
VL  - 37
IS  - 4
SP  - 544
EP  - 554
PB  - Wiley
CY  - New York
ER  - 
TY  - JOUR
A1  - Kraus, Sara Milena
A1  - Mathew-Stephen, Mariet
A1  - Schapranow, Matthieu-Patrick
T1  - Eatomics
BT  - Shiny exploration of quantitative proteomics data
JF  - Journal of proteome research
N2  - Quantitative proteomics data are becoming increasingly more available, and as a consequence are being analyzed and interpreted by a larger group of users. However, many of these users have less programming experience. Furthermore, experimental designs and setups are getting more complicated, especially when tissue biopsies are analyzed. Luckily, the proteomics community has already established some best practices on how to conduct quality control, differential abundance analysis and enrichment analysis. However, an easy-to-use application that wraps together all steps for the exploration and flexible analysis of quantitative proteomics data is not yet available. For Eatomics, we utilize the R Shiny framework to implement carefully chosen parts of established analysis workflows to (i) make them accessible in a user-friendly way, (ii) add a multitude of interactive exploration possibilities, and (iii) develop a unique experimental design setup module, which interactively translates a given research hypothesis into a differential abundance and enrichment analysis formula. In this, we aim to fulfill the needs of a growing group of inexperienced quantitative proteomics data analysts. Eatomics may be tested with demo data directly online via https://we.analyzegenomes.com/now/eatomics/or with the user's own data by installation from the Github repository at https://github.com/Millchmaedchen/Eatomics.
KW  - R Shiny
KW  - application
KW  - label-free
KW  - proteomics
KW  - analysis
KW  - differential
KW  - abundance
KW  - experimental design
Y1  - 2021
U6  - https://doi.org/10.1021/acs.jproteome.0c00398
SN  - 1535-3893
SN  - 1535-3907
VL  - 20
IS  - 1
SP  - 1070
EP  - 1078
PB  - American Chemical Society
CY  - Washington
ER  -