individual sequences and examine the cross-sectional distribution of these characteristics. Main indicators of individual sequences Basic measures Length Number of states visited Number of transitions (length of sequence of distinct successive states, DSS) Number of subsequences Recurrence Diversity Within sequence entropy Variance of spell duration Complexity of the sequence structure Volatility Complexity index Turbulence Measures that take account of the nature of the states Normative volatility i.e. proportion of positive spells. Integration index also known as Quality index Degradation Badness Precarity index Insecurity Other overall descriptive measures Mean time in the different states (overall state distribution) and their standard errors Transition probabilities between states. Visualization State sequences can nicely be rendered graphically and such plots prove useful for interpretation purposes. As shown above, the two basic plots are the index plot that renders individual sequences and the chronogram that renders the evolution of the cross-sectional state distribution along the timeframe. Chronograms (also known as status proportion plot or state distribution plot) completely overlook the diversity of the sequences, while index plots are often too scattered to be readable. Relative frequency plots and plots of representative sequences attempt to increase the readability of index plots without falling in the oversimplification of a chronogram. In addition, there are many plots that focus on specific characteristics of the sequences. Below is a list of plots that have been proposed in the literature for rendering large sets of sequences. For each plot, we give examples of software (details in section Software) that produce it. Index plot: renders the set of individual sequences (SADI, SQ, TraMineR) Chronogram (status proportion plot, state distribution plot): renders the sequence of cross-sectional distributions (SADI, SQ, TraMineR) Plot of multichannel sequences grouped by channels (seqHMM) or by individuals Plot of time series of cross-sectional indicators (entropy, modal state, ...) (SQ, TraMineR) Frequency plot (SQ, TraMineR) Relative frequency plot (TraMineRextras) Representative sequences (TraMineR) Mean time in the different states and their standard errors (TraMineR) State survival plot (TraMineRextras) Transition patterns (SADI) Transition plot (SQ; Gmisc) and plot of transition probabilities (seqHMM) Parallel coordinate plot (TraMineR, SQ) Probabilistic suffix trees (PST) Sequence networks (see social network analysis) (Software?) Narrative networks (Software?) Pairwise dissimilarities Pairwise dissimilarities between sequences serve to compare sequences and many advanced SA methods are based on these dissimilarities. The most popular dissimilarity measure is optimal matching (OM), i.e. the minimal cost of transforming one sequence into the other by