The poolr package contains functions for pooling/combining the results (i.e., p-values) from (dependent) hypothesis tests. Included are Fisher's method, Stouffer's method, the inverse chi-square method, the Bonferroni method, Tippett's method, and the binomial test. Each method can be adjusted based on an estimate of the effective number of tests or using empirically-derived null distribution using pseudo replicates. For Fisher's, Stouffer's, and the inverse chi-square method, direct generalizations based on multivariate theory are also available (leading to Brown's method, Strube's method, and the generalized inverse chi-square method).
Note that you can also read the documentation of the package online at https://ozancinar.github.io/poolr/ (where it is nicely formatted, equations are shown correctly, and the output from all examples is provided).
Brown, M. B. (1975). 400: A method for combining non-independent, one-sided tests of significance. Biometrics, 31(4), 987-992.
Fisher, R. A. (1932). Statistical Methods for Research Workers (4th ed.). Edinburgh: Oliver and Boyd.
Lancaster, H. O. (1961). The combination of probabilities: An application of orthonormal functions. Australian Journal of Statistics, 3(1), 20-33.
Strube, M. J. (1985). Combining and comparing significance levels from nonindependent hypothesis tests. Psychological Bulletin, 97(2), 334-341.
Tippett, L. H. C. (1931). Methods of Statistics. London: Williams Norgate.
Wilkinson, B. (1951). A statistical consideration in psychological research. Psychological Bulletin, 48(2), 156-158.