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Table 1.

Overview of ancestral recombination graph inference methods for studying introgression

Method	Scalability	Requires polarized data	Requires phased data	Mutation rate data	Recombination rate data	Demographic parameters
ARGweaver	Up to ∼50 individuals.	No.	No.	Point estimate or map.	Point estimate or map.	Point estimate of N_e or piecewise constant N_e estimates over time.
Protocol: Hubisz and Siepel (2020).
ARGweaver-D	Up to ∼50 individuals.	No.	No.	Point estimate or map.	Point estimate or map.	N_e estimates, split times, migration events.
Data: Introgression maps from Hubisz et al. (2020).
SARGE	Thousands of individuals.	Yes.	Yes.	No.	No.	N/A
N/A
tsinfer/tsdate	Thousands of individuals.	Yes.	Yes.	Point estimate.	Point estimate or map.	Point estimate of N_e or piecewise constant N_e estimates over time.
Data: Inferred genealogies from Wohns et al. (2022).

[i] For each method, we provide the link to its documentation, the number of individuals to whom it scales, note whether polarizing ancestral states and phasing are required, whether mutation or recombination rate estimates (or maps) are needed, any additional required demographic parameters, and links to publicly available resources. These resources include published protocols and data sets, located in the second row per method. Note that the methods appear in the order in which they are referenced in the text, and all associated URL links are provided in the “Data sets” section.