PT - JOURNAL ARTICLE AU - Jonathan Chang AU - Michael E. Alfaro TI - Crowdsourced geometric morphometrics enable rapid large-scale collection and analysis of phenotypic data AID - 10.1101/023382 DP - 2015 Jan 01 TA - bioRxiv PG - 023382 4099 - http://biorxiv.org/content/early/2015/07/28/023382.short 4100 - http://biorxiv.org/content/early/2015/07/28/023382.full AB - Advances in genomics and informatics have enabled the production of large phylogenetic trees. However, the ability to collect large phenotypic datasets has not kept pace.Here, we present a method to quickly and accurately gather morphometric data using crowdsourced image-based landmarking.We find that crowdsourced workers perform similarly to experienced morphologists on the same digitization tasks. We also demonstrate the speed and accuracy of our method on seven families of ray-finned fishes (Actinopterygii).Crowdsourcing will enable the collection of morphological data across vast radiations of organisms, and can facilitate richer inference on the macroevolutionary processes that shape phenotypic diversity across the tree of life.