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  -