Sequence analysis was originally invented by biologists with the aim of comparing DNA sequences in order to find out to what extent two DNA strands are homologous to each other or, in other words, to determine the distance between them (Kruskal 1983). The established degree of similarity then allows for conclusions about a common ancestor of two DNA strands. The initial utilization of sequence analysis in sociology was made in the 1980s, with Andrew Abbott’s work on musicians’ careers and ritual dances (Abbott 1983; Abbott and Forrest 1986). Here, sequence analysis was seen as a more qualitative tool in the context of historical, narrative sociology. Due to the limited capacity of computers, analysis was restricted to only a few cases with short sequences. With increasing technological development in the 1990s, researchers began to focus on individual sequences, such as class careers (Halpin and Chan 1998), employment biographies (Abbott and Hrycak 1990; Blair-Loy 1999; Pollock, Antcliff, and Ralphs 2002), family histories (Elzinga and Liefbroer 2007), school-to-work transitions (Scherer 2001; Schoon et al. 2001; McVicar and Anyadike-Danes 2002; BrzinskyFay 2007), and life-course trajectories (Billari and Piccarreta 2005; Wiggins et al. 2007; Martin, Schoon, and Ross 2008). The technical situation improved further with both increasing processor speed and wider availability of software implementations, such as the various implementations of sequence analysis in the Stata package, which enabled more researchers from different disciplines to compare sequences of large numbers of individuals, finding out similarities, quantifying certain characteristics, or grouping Editorial