Description: Automatically displays graphical visualization for exported data table (permutated results) from Connectivity Map (CMap) (2006) <doi:10.1126/science.1132939>.

Title: Matching Algorithms for Causal Inference with Clustered Data
Authors@R: c(person("Massimo", "Cannas", role = c("aut", "cre"),
person("Elena", "Colicino", role = "ctb",
Author: Massimo Cannas [aut, cre], Elena Colicino [ctb]
Description: Provides functions to perform matching algorithms for causal inference with clustered data, as described in B. Arpino and M. Cannas (2016) <doi:10.1002/sim.6880>. Pure within-cluster and preferential-within cluster matching are implemented. Both algorithms provide causal estimates with cluster-adjusted estimates of standard errors.

person("Bruno", "Arpino", role = c("ctb"),
Author: Massimo Cannas [aut, cre], Elena Colicino [ctb], Bruno Arpino [ctb]
Description: Provides functions to perform matching algorithms for causal inference with clustered data, as described in B. Arpino and M. Cannas (2016) <doi:10.1002/sim.6880>. Pure within-cluster and preferential within-cluster matching are implemented. Both algorithms provide causal estimates with cluster-adjusted estimates of standard errors.

person("Elena", "Colicino", role = c("ctb"),

Description: To visualize the results of Genome-Wide Association Study, Manhattan plot was born. However, it will take much time to draw an elaborate one. Here, this package gives a function named "CMplot" can easily solve the problem. Inputting the results of GWAS and adjusting certain parameters, users will obtain the desired Manhattan plot. Also, a circle Manhattan plot is first put forward, which demonstrates multiple traits in one circle plot. A more visualized figure can spare the length of a paper and lift the paper to a higher level.

Description: Manhattan plot, a type of scatter plot, was widely used to display the association results. However, it is usually time-consuming and laborious for a
non-specialist user to write scripts and adjust parameters of an elaborate plot. Moreover, the ever-growing traits measured have necessitated the
integration of results from different Genome-wide association study researches. Circle Manhattan Plot is the first open R package that can lay out
Genome-wide association study P-value results in both traditional rectangular patterns and novel circular ones. United in only one bull's eye style
plot, association results from multiple traits can be compared interactively, thereby to reveal both similarities and differences between signals.