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Merge pull request #30 from MoseleyBioinformaticsLab/rows_features
updates main functionality to columnar samples
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DESCRIPTION

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Package: visualizationQualityControl
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Version: 0.4.11
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Version: 0.5.1
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Title: Development of visualization methods for quality control
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Description: Provides utilities useful quality control of
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high-throughput -omics datasets.
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Authors@R: c(person(given = c("Robert", "M"), family = "Flight", email
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= "[email protected]", role = c("aut", "cre")), person(given
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= c("Hunter", "NB"), family = "Moseley", email =
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"[email protected]", role = c("aut")))
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Date: 2021-12-28
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Date: 2024-02-15
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Depends: R (>= 3.1.1)
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biocViews:
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Imports: ComplexHeatmap (>= 1.2.1), stats, dendsort, colorspace, dplyr,
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ggplot2, broom, knitrProgressBar, magrittr, purrr
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License: MIT + file LICENSE
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VignetteBuilder: knitr
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Suggests: testthat, knitr, rmarkdown, circlize, viridis, ICIKendallTau,
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ggforce
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Suggests: testthat, knitr, rmarkdown, circlize, viridis, ICIKendallTau
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(>= 1.0.0), ggforce
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RoxygenNote: 7.2.3
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Encoding: UTF-8
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LinkingTo: Rcpp

NAMESPACE

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export(calc_sd_rsd)
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export(calc_sd_rsd_nls)
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export(calculate_fratio)
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export(calculate_weights)
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export(correspondence)
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export(count_matching_features)
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export(determine_outliers)
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export(filter_non_zero_percentage)
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export(generate_group_colors)
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export(globally_it_weighted_pairwise_correlation)
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export(information_volume)
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export(keep_non_missing_percentage)
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export(keep_non_zero_percentage)
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export(locally_it_weighted_pairwise_correlation)
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export(median_class_correlations)
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export(median_correlations)
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export(outlier_fraction)
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export(pairwise_correlation)
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export(pairwise_correlation_both0)
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export(pairwise_correlation_counts)
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export(pairwise_correlation_multicore)
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export(pairwise_distance)
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export(pairwise_nonzero)
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export(similarity_reorder)
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export(similarity_reorderbyclass)
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export(split_groups)

NEWS.md

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# vsualizationQualityControl 0.4.11
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# visualizationQualityControl 0.5.0
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* Changed some functions to treat columns as samples and rows as features:
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* `keep_non_zero_percentage`
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* `summarize_data`
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* `calculate_fratio`
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* Added `keep_non_missing_percentage`, which allows using multiple values to represent missingnes.
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* Made `summarize_data` handle possible missing values.
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* Removed correlation calculation functions, those have been superseded by [ICIKendallTau](https://moseleybioinformaticslab.github.io/ICIKendallTau/).
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# visualizationQualityControl 0.4.11
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* Added a new argument `only_high` to `determine_outliers` to only look at the high end of the score distribution for outliers, as sometimes `boxplot.stats` will pick up outliers at the low end as well.
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