Reading this (Wang et al. 2010), in particular Supp. report 4. Has to do with bootstrapping population estimates using the different enzymes used to find integration sites.
The review (here A. Chao 2001) indicates sample coverage approaches may be most appropriate for models where the capture probabilities can vary both over time and between species (which is certainly the case for estimating populations from longitudinal T cell sequencing data). I'll need to read more (esp. (Tsay and Chao 2001) and (Chao and Tsay 1998)).
Also found the package Rcapture which appears to fit a Poisson regression to incident counts. I've gotten it to work (kind of) but R crashed trying to plot the model so I'll need to come back to this. If memory serves, it was substantially more conservative in its estimates than the Chao2 estimate.
Chao, A, and P K Tsay. 1998. “A sample coverage approach to multiple-system estimation with application to census undercount.” Journal of the American Statistical Association 93 (441): 283–93. doi:10.2307/2669624.
Chao, Anne. 2001. “An overview of closed capture-recapture models.” Journal of Agricultural, Biological, and Environmental Statistics 6 (2). Springer-Verlag: 158–75. doi:10.1198/108571101750524670.
Tsay, P K, and A Chao. 2001. “Population size estimation for capture - recapture models with applications to epidemiological data.” Journal of Applied Statistics 28 (1): 25–36. http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=mekentosj&SrcApp=Papers&DestLinkType=FullRecord&DestApp=WOS&KeyUT=000165844500002.
Wang, Gary P, Charles C Berry, Nirav Malani, Philippe Leboulch, Alain Fischer, Salima Hacein-Bey-Abina, Marina Cavazzana-Calvo, and Frederic D Bushman. 2010. “Dynamics of gene-modified progenitor cells analyzed by tracking retroviral integration sites in a human SCID-X1 gene therapy trial.” Blood 115 (22): 4356–66. doi:10.1182/blood-2009-12-257352.