The congeneric normal-ogive model is a popular model for
psychometric data (McDonald, R. P. (1997) <doi:10.1007/978-1-4757-2691-6_15>).
This model estimates the model, calculates theoretical and concrete
reliability coefficients, and predicts the latent variable of the model.
This is the companion package to Moss (2020) <doi:10.31234/osf.io/nvg5d>.

c(person("Viktor","Petukhov", email="viktor.s.petuhov@ya.ru", role="aut"), person("Nikolas","Barkas", email="nikolas_barkas@hms.harvard.edu", role="aut"), person("Peter", "Kharchenko", email = "peter_kharchenko@hms.harvard.edu", role = "aut"), person("Weiliang", "Qiu", email = "weiliang.qiu@gmail.com", role = c("ctb")), person("Evan", "Biederstedt", email="evan.biederstedt@gmail.com", role=c("aut", "cre")))
Wires together large collections of single-cell RNA-seq datasets, which allows for both the identification of recurrent cell clusters and the propagation of information between datasets in multi-sample or atlas-scale collections. 'Conos' focuses on the uniform mapping of homologous cell types across heterogeneous sample collections. For instance, users could investigate a collection of dozens of peripheral blood samples from cancer patients combined with dozens of controls, which perhaps includes samples of a related tissue such as lymph nodes. This package interacts with data available through the 'conosPanel' package, which is available in a 'drat' repository. To access this data package, see the instructions at <https://github.com/kharchenkolab/conos>. The size of the 'conosPanel' package is approximately 12 MB.
See the file COPYRIGHTS for various conos copyright details
abind, cowplot, ComplexHeatmap, dendextend, dplyr, ggplot2,
ggrepel, gridExtra, irlba, leidenAlg, magrittr, Matrix.utils,
methods, N2R, parallel, R6, reshape2, rlang, Rtsne, sccore (>=
0.1.1), stats, tools, utils
AnnotationDbi, BiocParallel, conosPanel, DESeq2, entropy,
ggrastr, GO.db, jsonlite, knitr, org.Hs.eg.db, org.Mm.eg.db,
p2data, pagoda2, pbapply, PMA, pROC, plyr, rhdf5, rmarkdown,
rmumps, Seurat, shinycssloaders, SummarizedExperiment,
testthat, tibble, uwot, zoo
Viktor Petukhov [aut],
Nikolas Barkas [aut],
Peter Kharchenko [aut],
Weiliang Qiu [ctb],
Evan Biederstedt [aut, cre]