This study examines characteristics of data sharing and data re-use in Genetics and Heredity, where data citation is most common. This study applies an exploratory method because data citation is a relatively new area. The Data Citation Index (DCI) on the Web of Science was selected because DCI provides a single access point to over 500 data repositories worldwide and to over two million data studies and datasets across multiple disciplines and monitors quality research data through a peer review process. We explore data citations for Genetics and Heredity, as a case study by examining formal citations recorded in the DCI and informally by sampling a selection of papers for implicit data citations within publications. Citer-based analysis is conducted in order to remedy self-citation in the data citation phenomena. We explore 148 sampled citing articles in order to identify factors that influence data sharing and data re-use, including references, main text, supplementary data/information, acknowledgments, funding information, author information, and web/author resources. This study is unique in that it relies on a citer-based analysis approach and by analyzing peer-reviewed and published data, data repositories, and citing articles of highly productive authors where data sharing is most prevalent. This research is intended to provide a methodological and practical contribution to the study of data citation.