@article{fdi:010049232,
  title = {{M}ulti{T}est {V}.1.2, a program to binomially combine independent tests and performance comparison with other related methods on proportional data},
  author = {{D}e {M}eeus, {T}hierry and {G}u{\'e}gan, {J}ean-{F}ran{\c{c}}ois and {T}eriokhin, {A}. {T}.},
  editor = {},
  language = {{ENG}},
  abstract = {{B}ackground: {C}ombining multiple independent tests, when all test the same hypothesis and in the same direction, has been the subject of several approaches. {B}esides the inappropriate (in this case) {B}onferroni procedure, the {F}isher's method has been widely used, in particular in population genetics. {T}his last method has nevertheless been challenged by the {SGM} (symmetry around the geometric mean) and {S}touffer's {Z}-transformed methods that are less sensitive to asymmetry and deviations from uniformity of the distribution of the partial {P}-values. {P}erformances of these different procedures were never compared on proportional data such as those currently used in population genetics. {R}esults: {W}e present new software that implements a more recent method, the generalised binomial procedure, which tests for the deviation of the observed proportion of {P}-values lying under a chosen threshold from the expected proportion of such {P}-values under the null hypothesis. {T}he respective performances of all available procedures were evaluated using simulated data under the null hypothesis with standard {P}-values distribution (differentiation tests). {A}ll procedures more or less behaved consistently with similar to 5% significant tests at alpha = 0.05. {T}hen, linkage disequilibrium tests with increasing signal strength (rate of clonal reproduction), known to generate highly nonstandard {P}-value distributions are undertaken and finally real population genetics data are analysed. {I}n these cases, all procedures appear, more or less equally, very conservative, though {SGM} seems slightly more conservative. {C}onclusion: {B}ased on our results and those discussed in the literature we conclude that the generalised binomial and {S}touffer's {Z} procedures should be preferred and {Z} when the number of tests is very small. {T}he more conservative {SGM} might still be appropriate for meta-analyses when a strong publication bias in favour of significant results is expected to inflate type 2 error.},
  keywords = {},
  booktitle = {},
  journal = {{B}mc {B}ioinformatics},
  volume = {10},
  numero = {},
  pages = {443},
  ISSN = {1471-2105},
  year = {2009},
  DOI = {10.1186/1471-2105-10-443},
  URL = {https://www.documentation.ird.fr/hor/fdi:010049232},
}