c(person("Hassan Roland", "Nasser", role = c("aut", "cre"),
email = "hassan.nasser@me.com"),
person("Marie", "Schneider", role = c("aut", "ctb"),
email = "marieschnellbaecher@outlook.de"),
person("Joanna", "Stachowicz ", role = c("aut", "rev"),
email = "joa.stachowi@gmail.com"),
person("Christina", "Umstaetter ", role = c("aut", "ths"),
email = "christina.umstaetter@thuenen.de"))
Hassan Roland Nasser [aut, cre],
Marie Schneider [aut, ctb],
Joanna Stachowicz [aut, rev],
Christina Umstaetter [aut, ths]

Tests for Detecting Irregular Digit Patterns
person(given = "Koen",
family = "Derks",
role = c("aut", "cre"),
email = "k.derks@nyenrode.nl",
comment = c(ORCID = '0000-0002-5533-9349'))
Provides statistical tests and support functions for detecting irregular digit patterns in numerical data. The package includes tools for extracting digits at various locations in a number, tests for repeated values, and (Bayesian) tests of digit distributions.
benford.analysis, BenfordTests, BeyondBenford, knitr,
rmarkdown, testthat

Deconvolution of Bulk RNA-Seq Data Based on Deep Learning
c(
person(given = "Diego", family = "Mañanes", email = "dmananesc@cnic.es", role = c("aut", "cre"), comment = c(ORCID = "0000-0001-7247-6794")),
person(given = "Carlos", family = "Torroja", email = "ctorroja@cnic.es", role = "aut", comment = c(ORCID = "0000-0001-8914-3400")),
person(given = "Fatima", family = "Sanchez-Cabo", email = "fscabo@cnic.es", role = "aut", comment = c(ORCID = "0000-0003-1881-1664")))
Deconvolution of bulk RNA-Seq data using context-specific deconvolution models based on Deep Neural Networks using scRNA-Seq data as input. These models are able to make accurate estimates of the cell composition of bulk RNA-Seq samples from the same context using the advances provided by Deep Learning and the meaningful information provided by scRNA-Seq data. See Torroja and Sanchez-Cabo (2017) <doi:10.3389/fgene.2019.00978> for more details.
rlang, Matrix, Matrix.utils, methods, tidyr,
SingleCellExperiment, SummarizedExperiment, splatter, zinbwave,
stats, pbapply, S4Vectors, dplyr, tools, reshape2, gtools,
edgeR, reticulate, keras, tensorflow, ggplot2, ggpubr,
RColorBrewer
knitr, rmarkdown, BiocParallel, rhdf5, DelayedArray,
DelayedMatrixStats, HDF5Array, testthat
Python (>= 2.7.0), TensorFlow
(https://www.tensorflow.org/)
'AllClasses.R' 'AllGenerics.R' 'digitalDLSorteR.R'
'dnnModel.R' 'evalMetrics.R' 'loadData.R' 'simBulk.R'
'simSingleCell.R' 'utils.R'