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fastTopics wrapper #151

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fd1ea6e
Working on FitTopicModel and fast_topics_demo example script.
pcarbo Jan 14, 2021
8baf086
Made a few small improvements to the fastTopics demo.
pcarbo Jan 14, 2021
4fb6cad
Filled out more of the roxygen2 docs for FitTopicModel.
pcarbo Jan 14, 2021
75e6240
Made several improvements to the roxygen2 docs for FitTopicModel, and…
pcarbo Jan 14, 2021
d362c19
Improved fasttopics example; fixed PCA reduction key.
pcarbo Jan 15, 2021
8a6b8ae
Revised the FitTopicModel roxygen2 docs.
pcarbo Jan 15, 2021
cd3f143
Completed fast_topics_demo.R script.
pcarbo Jan 15, 2021
811d618
First build of the fasttopics vignette.
pcarbo Jan 15, 2021
8dee481
More additions to the fasttopics vignette.
pcarbo Jan 15, 2021
da9b1c9
Some minor adjustments to the fasttopics vignette.
pcarbo Jan 15, 2021
737a8fc
Made a few small revisions to the vignette.
pcarbo Jan 15, 2021
ccccf1b
Added fastTopics to README.
pcarbo Jan 15, 2021
023a5db
Added vignette title in README.
pcarbo Jan 15, 2021
3988ce4
A couple of small edits to the fasttopics code.
pcarbo Jan 15, 2021
080fd0e
Fixed PCA plot in fasttopics vignette.
pcarbo Jan 16, 2021
0482d57
Implemented helper functions prepare_counts_fasttopics and pca_from_l…
pcarbo Jan 18, 2021
dba8308
Implemented FitPoissonNMF.
pcarbo Jan 18, 2021
a61ad95
Filled out roxygen2 docs for FitPoissonNMF.
pcarbo Jan 19, 2021
c604eb4
Added notes from Alan.
pcarbo Feb 19, 2021
c665ccb
Added notes from Gilad Green.
pcarbo Feb 25, 2021
dd848d0
Added reduction.pca.name and reduction.pca.key arguments to fastTopic…
pcarbo Mar 3, 2021
5667953
Added docs/fasttopics_files.
pcarbo Mar 3, 2021
1bad1f7
Updated verbose argument in FitTopicModel and FitPoissonNMF.
pcarbo Mar 4, 2021
bb7a4a4
Merge remote-tracking branch 'upstream/master'.
pcarbo Mar 15, 2023
eefec42
Removed .DS_Store.
pcarbo Mar 15, 2023
1459754
Added fastTopics to READMEs.
pcarbo Mar 15, 2023
91d130b
Added link to README.
pcarbo Mar 15, 2023
6d1ac21
Updated citations in fasttopics vignette.
pcarbo Mar 15, 2023
6fe8cf6
Merge branch 'master' of github.com:stephenslab/seurat-wrappers.
pcarbo Mar 15, 2023
88660d2
Rebuilt the fasttopics vignettes.
pcarbo Mar 15, 2023
e1f5537
Fixed the formatting of the citations in the fasttopics vignette.
pcarbo Mar 15, 2023
00e1c2b
Merge branch 'master' of github.com:stephenslab/seurat-wrappers.
pcarbo Mar 15, 2023
4304d5e
A few small edits to the fasttopics vignette.
pcarbo Mar 15, 2023
c48f7df
Rebuilt html for fasttopics vignette.
pcarbo Mar 15, 2023
969f01a
A few small revisions to the fasttopics vignette.
pcarbo Mar 16, 2023
2f1a0a9
Merge branch 'master' of github.com:stephenslab/seurat-wrappers.
pcarbo Mar 16, 2023
d23470c
Rebuilt the fasttopics vignette html.
pcarbo Mar 16, 2023
43dd380
Small fix to the fasttopics rmd.
pcarbo Mar 16, 2023
4bba11b
Added some text to the vignette explaining the structure plot.
pcarbo Mar 16, 2023
3fdf833
Regenerated the markdown and html for fasttopics; the html is no long…
pcarbo Mar 16, 2023
c260284
Fixed a comment in the fasttopics vignette.
pcarbo Mar 17, 2023
12b6e79
A few edits to the text in the fasttopics vignette.
pcarbo Mar 17, 2023
cfda992
Started implementation of PerformGoMDEAnalysis.
pcarbo Mar 17, 2023
20559ce
Updated roxygen2 for FitPoissonNMF and FitTopicModel.
pcarbo Mar 17, 2023
0cbc485
Filled out most of the implementation for PerformGoMDEAnalysis.
pcarbo Mar 17, 2023
44dc860
Revised the misc slot for the dimreduc objects in the fasttopics func…
pcarbo Mar 17, 2023
72856db
Updated the html for the fasttopics vignette.
pcarbo Mar 17, 2023
4fe0277
Added volcano plots to the fasttopics vignette.
pcarbo Mar 18, 2023
54c2832
Rebuilt fasttopics vignette.
pcarbo Mar 18, 2023
4645464
A few fixes to the fasttopics rmd.
pcarbo Mar 18, 2023
107d766
A few edits to the fasttopics vignette.
pcarbo Mar 20, 2023
f2eb308
Merge branch 'master' of github.com:stephenslab/seurat-wrappers.
pcarbo Mar 20, 2023
305f434
Small edit to the fasttopics vignette.
pcarbo Mar 20, 2023
cd1c678
Revised the volcano plots and accompanying text in the fasttopics vig…
pcarbo Mar 20, 2023
c763916
Rebuilt the fasttopics md vignette.
pcarbo Mar 20, 2023
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Rebuilt the fasttopics vignettes.
pcarbo committed Mar 15, 2023

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commit 88660d286445875f5452c2a4fb054befcd9498ec
2 changes: 1 addition & 1 deletion DESCRIPTION
Original file line number Diff line number Diff line change
@@ -61,7 +61,7 @@ Collate:
'velocity.R'
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
RoxygenNote: 7.1.2
Suggests:
cipr,
conos,
6 changes: 3 additions & 3 deletions NAMESPACE
Original file line number Diff line number Diff line change
@@ -7,9 +7,9 @@ S3method(as.Seurat,cell_data_set)
S3method(as.Seurat,list)
S3method(as.cell_data_set,Seurat)
export(ALRAChooseKPlot)
export(ExportToCellbrowser)
export(FitPoissonNMF)
export(FitTopicModel)
export(ExportToCellbrowser)
export(PlotMiQC)
export(ReadAlevin)
export(ReadVelocity)
@@ -67,11 +67,11 @@ importFrom(Seurat,as.Graph)
importFrom(Seurat,as.Seurat)
importFrom(Seurat,as.SingleCellExperiment)
importFrom(cowplot,theme_cowplot)
importFrom(fastTopics,fit_poisson_nmf)
importFrom(fastTopics,fit_topic_model)
importFrom(data.table,data.table)
importFrom(data.table,fwrite)
importFrom(data.table,setDTthreads)
importFrom(fastTopics,fit_poisson_nmf)
importFrom(fastTopics,fit_topic_model)
importFrom(ggplot2,aes_string)
importFrom(ggplot2,geom_line)
importFrom(ggplot2,geom_point)
287 changes: 162 additions & 125 deletions docs/fasttopics.html

Large diffs are not rendered by default.

243 changes: 122 additions & 121 deletions docs/fasttopics.md
Original file line number Diff line number Diff line change
@@ -1,7 +1,3 @@
Analyzing Seurat data using fastTopics
================
Compiled: January 15, 2021

Here we illustrate the use of the
[fastTopics](https://github.com/stephenslab/fastTopics) Seurat wrapper
to analyze a Seurat data set. This vignette is only intended to
@@ -13,161 +9,166 @@ vignettes](https://stephenslab.github.io/fastTopics/articles).
If you find the **fastTopics** package useful for your work, please
cite:

Kushal K. Dey, Chiaowen Joyce Hsiao and Matthew Stephens (2017).
[Visualizing the structure of RNA-seq expression data using grade of
membership models.](https://doi.org/10.1371/journal.pgen.1006599) *PLoS
Genetics* **13**, e1006599.
K. K. Dey, C. Joyce Hsiao and M. Stephens (2017). [Visualizing the
structure of RNA-seq expression data using grade of membership
models.](https://doi.org/10.1371/journal.pgen.1006599) PLoS Genetics 13,
e1006599.

P. Carbonetto, A. Sarkar, Z. Wang and M. Stephens (2021). [Non-negative
matrix factorization algorithms greatly improve topic model
fits.](https://arxiv.org/abs/2105.13440) arXiv 2105.13440

If you used the `de_analysis` function in fastTopics, please cite:

Peter Carbonetto, Kevin Luo, Kushal Dey, Joyce Hsiao and Matthew
Stephens (2021). fastTopics: fast algorithms for fitting topic models
and non-negative matrix factorizations to count data. R package version
0.4-23. <https://github.com/stephenslab/fastTopics>
P. Carbonetto, K. Luo, A. Sarkar, A. Hung, K. Tayeb, S. Pott and M.
Stephens (2023). [Interpreting structure in sequence count data with
differential expression analysis allowing for grades of
membership.](https://doi.org/10.1101/2023.03.03.531029) bioRxiv
<doi:10.1101/2023.03.03.531029>

We begin by loading the packages used to perform the analysis.

``` r
library(Seurat)
library(SeuratData)
library(SeuratWrappers)
library(fastTopics)
library(cowplot)
```
library(Seurat)
library(SeuratData)
library(SeuratWrappers)
library(fastTopics)
library(cowplot)

We set the seed so that the results can be reproduced.

``` r
set.seed(1)
```
set.seed(1)

Load—and, if necessary, install—the PBMC 3k data set containing
transcription profiles for 2,700 cells.

``` r
InstallData("pbmc3k")
data(pbmc3k)
dim(GetAssayData(pbmc3k))
# [1] 13714 2700
```
InstallData("pbmc3k")
data(pbmc3k)
dim(GetAssayData(pbmc3k))
# [1] 13714 2700

Fit the multinomial topic model to the raw UMI counts—*no pre-processing
or pre-selection of genes is needed.* Note that it may take several
minutes to complete this model fitting step.

``` r
pbmc3k <- FitTopicModel(pbmc3k,k = 6)
```
pbmc3k <- FitTopicModel(pbmc3k,k = 6)

To fit a topic model, we must specify \(K\), the number of topics. Here,
we have chosen \(K = 6\) topics. In most settings, a good choice of
\(K\) will not be known in advance, so you will you want to explore the
results from topic models at different settings of \(K\).
To fit a topic model, we must specify *K*, the number of topics. Here,
we have chosen *K* = 6 topics. In most settings, a good choice of *K*
will not be known in advance, so you will you want to explore the
results from topic models at different settings of *K*.

This plot shows the cells projected onto the top two principal
components (PCs) of the topic mixture proportions.

``` r
Idents(pbmc3k) <- pbmc3k$seurat_annotations
DimPlot(pbmc3k,reduction = "pca_topics",pt.size = 1) +
theme_cowplot(font_size = 10)
```
Idents(pbmc3k) <- pbmc3k$seurat_annotations
DimPlot(pbmc3k,reduction = "pca_topics",pt.size = 1) +
theme_cowplot(font_size = 10)

<img src="fasttopics_files/figure-gfm/pca-1-1.png" style="display: block; margin: auto;" />
<img src="fasttopics_files/figure-markdown_strict/pca-1-1.png" style="display: block; margin: auto;" />

Compare this against the top two PCs of the transformed counts:

``` r
pbmc3k <- FindVariableFeatures(pbmc3k)
pbmc3k <- NormalizeData(pbmc3k)
pbmc3k <- ScaleData(pbmc3k)
pbmc3k <- RunPCA(pbmc3k)
DimPlot(pbmc3k,reduction = "pca",pt.size = 1) +
theme_cowplot(font_size = 10)
```
pbmc3k <- FindVariableFeatures(pbmc3k)
pbmc3k <- NormalizeData(pbmc3k)
pbmc3k <- ScaleData(pbmc3k)
pbmc3k <- RunPCA(pbmc3k)
DimPlot(pbmc3k,reduction = "pca",pt.size = 1) +
theme_cowplot(font_size = 10)

<img src="fasttopics_files/figure-gfm/pca-2-1.png" style="display: block; margin: auto;" />
<img src="fasttopics_files/figure-markdown_strict/pca-2-1.png" style="display: block; margin: auto;" />

The fitted topic model—a “multinom\_topic\_model” object—is stored in
the “misc” slot:

``` r
fit <- Misc(Reductions(pbmc3k,"multinom_topic_model"))
```
fit <- Misc(Reductions(pbmc3k,"multinom_topic_model"))

Once the fitted topic model is extracted, many functions from the
**fastTopics** package can be used for analysis and visualization. For
example, the Structure plot provides an evocative visual summary of the
estimated mixture proportions for each cell. Here, we have grouped the
cells by previously inferred
labels.
cells by previously inferred labels.

``` r
structure_plot(fit,grouping = Idents(pbmc3k),gap = 25)
```
structure_plot(fit,grouping = Idents(pbmc3k),gap = 25)

<img src="fasttopics_files/figure-gfm/structure-plot-1.png" style="display: block; margin: auto;" />
<img src="fasttopics_files/figure-markdown_strict/structure-plot-1.png" style="display: block; margin: auto;" />

This is the version of R and the packages that were used to generate
these results.

``` r
sessionInfo()
# R version 3.6.2 (2019-12-12)
# Platform: x86_64-apple-darwin15.6.0 (64-bit)
# Running under: macOS Catalina 10.15.7
#
# Matrix products: default
# BLAS: /Library/Frameworks/R.framework/Versions/3.6/Resources/lib/libRblas.0.dylib
# LAPACK: /Library/Frameworks/R.framework/Versions/3.6/Resources/lib/libRlapack.dylib
#
# locale:
# [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
#
# attached base packages:
# [1] stats graphics grDevices utils datasets methods base
#
# other attached packages:
# [1] cowplot_1.0.0 fastTopics_0.4-23 SeuratWrappers_0.3.2
# [4] pbmc3k.SeuratData_3.1.4 SeuratData_0.2.1 Seurat_3.2.3
#
# loaded via a namespace (and not attached):
# [1] Rtsne_0.15 colorspace_1.4-1 deldir_0.1-29
# [4] ggridges_0.5.2 spatstat.data_1.4-3 farver_2.0.1
# [7] leiden_0.3.3 listenv_0.8.0 remotes_2.1.0
# [10] MatrixModels_0.4-1 ggrepel_0.9.0 fansi_0.4.0
# [13] codetools_0.2-16 splines_3.6.2 knitr_1.26
# [16] polyclip_1.10-0 zeallot_0.1.0 jsonlite_1.6
# [19] mcmc_0.9-6 ica_1.0-2 cluster_2.1.0
# [22] png_0.1-7 uwot_0.1.10 shiny_1.4.0
# [25] sctransform_0.3.2 BiocManager_1.30.10 compiler_3.6.2
# [28] httr_1.4.2 backports_1.1.5 assertthat_0.2.1
# [31] Matrix_1.2-18 fastmap_1.0.1 lazyeval_0.2.2
# [34] cli_2.0.0 later_1.0.0 prettyunits_1.1.1
# [37] htmltools_0.4.0 quantreg_5.54 tools_3.6.2
# [40] rsvd_1.0.2 igraph_1.2.5 coda_0.19-3
# [43] gtable_0.3.0 glue_1.3.1 RANN_2.6.1
# [46] reshape2_1.4.3 dplyr_0.8.3 rappdirs_0.3.1
# [49] Rcpp_1.0.5 spatstat_1.64-1 scattermore_0.7
# [52] vctrs_0.2.1 nlme_3.1-142 lmtest_0.9-38
# [55] xfun_0.11 stringr_1.4.0 globals_0.13.0
# [58] mime_0.8 miniUI_0.1.1.1 lifecycle_0.1.0
# [61] irlba_2.3.3 goftest_1.2-2 future_1.18.0
# [64] MASS_7.3-51.4 zoo_1.8-7 scales_1.1.0
# [67] hms_0.5.2 promises_1.1.0 spatstat.utils_1.17-0
# [70] parallel_3.6.2 SparseM_1.78 RColorBrewer_1.1-2
# [73] yaml_2.2.0 reticulate_1.16 pbapply_1.4-3
# [76] gridExtra_2.3 ggplot2_3.3.0 rpart_4.1-15
# [79] stringi_1.4.3 rlang_0.4.5 pkgconfig_2.0.3
# [82] matrixStats_0.56.0 evaluate_0.14 lattice_0.20-38
# [85] ROCR_1.0-11 purrr_0.3.3 tensor_1.5
# [88] labeling_0.3 patchwork_1.0.1 htmlwidgets_1.5.1
# [91] tidyselect_0.2.5 RcppAnnoy_0.0.18 plyr_1.8.5
# [94] magrittr_1.5 R6_2.4.1 pillar_1.4.3
# [97] mgcv_1.8-31 fitdistrplus_1.1-1 survival_3.1-8
# [100] abind_1.4-5 tibble_2.1.3 future.apply_1.6.0
# [103] crayon_1.3.4 KernSmooth_2.23-16 plotly_4.9.2
# [106] rmarkdown_2.3 progress_1.2.2 grid_3.6.2
# [109] data.table_1.12.8 digest_0.6.23 xtable_1.8-4
# [112] tidyr_1.0.0 httpuv_1.5.2 MCMCpack_1.4-5
# [115] RcppParallel_4.4.2 munsell_0.5.0 viridisLite_0.3.0
# [118] quadprog_1.5-8
```
sessionInfo()
# R version 4.2.0 (2022-04-22)
# Platform: x86_64-pc-linux-gnu (64-bit)
# Running under: Red Hat Enterprise Linux 8.4 (Ootpa)
#
# Matrix products: default
# BLAS/LAPACK: /software/openblas-0.3.13-el8-x86_64/lib/libopenblas_skylakexp-r0.3.13.so
#
# locale:
# [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
# [3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
# [5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8
# [7] LC_PAPER=en_US.UTF-8 LC_NAME=C
# [9] LC_ADDRESS=C LC_TELEPHONE=C
# [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
#
# attached base packages:
# [1] stats graphics grDevices utils datasets methods base
#
# other attached packages:
# [1] rmarkdown_2.14 SeuratWrappers_0.3.1 pbmc3k.SeuratData_3.1.4
# [4] cowplot_1.1.1 fastTopics_0.6-150 SeuratData_0.2.2
# [7] SeuratObject_4.1.3 Seurat_4.3.0
#
# loaded via a namespace (and not attached):
# [1] utf8_1.2.2 spatstat.explore_3.0-6 reticulate_1.24
# [4] R.utils_2.11.0 tidyselect_1.1.2 htmlwidgets_1.5.4
# [7] grid_4.2.0 Rtsne_0.16 devtools_2.4.3
# [10] munsell_0.5.0 codetools_0.2-18 ica_1.0-2
# [13] future_1.25.0 miniUI_0.1.1.1 withr_2.5.0
# [16] spatstat.random_3.1-3 colorspace_2.0-3 progressr_0.10.0
# [19] highr_0.9 knitr_1.39 rstudioapi_0.13
# [22] ROCR_1.0-11 tensor_1.5 listenv_0.8.0
# [25] labeling_0.4.2 mixsqp_0.3-48 polyclip_1.10-0
# [28] MCMCpack_1.6-3 farver_2.1.0 rprojroot_2.0.3
# [31] coda_0.19-4 parallelly_1.31.1 vctrs_0.4.1
# [34] generics_0.1.2 xfun_0.30 R6_2.5.1
# [37] rsvd_1.0.5 invgamma_1.1 spatstat.utils_3.0-1
# [40] cachem_1.0.6 assertthat_0.2.1 promises_1.2.0.1
# [43] scales_1.2.0 gtable_0.3.0 globals_0.14.0
# [46] processx_3.5.3 goftest_1.2-3 mcmc_0.9-7
# [49] rlang_1.0.2 MatrixModels_0.5-0 splines_4.2.0
# [52] lazyeval_0.2.2 spatstat.geom_3.0-6 BiocManager_1.30.20
# [55] yaml_2.3.5 reshape2_1.4.4 abind_1.4-5
# [58] httpuv_1.6.5 tools_4.2.0 usethis_2.1.5
# [61] ggplot2_3.3.6 ellipsis_0.3.2 jquerylib_0.1.4
# [64] RColorBrewer_1.1-3 sessioninfo_1.2.2 ggridges_0.5.3
# [67] Rcpp_1.0.9 plyr_1.8.7 progress_1.2.2
# [70] purrr_0.3.4 ps_1.7.0 prettyunits_1.1.1
# [73] deldir_1.0-6 pbapply_1.5-0 ashr_2.2-54
# [76] zoo_1.8-10 ggrepel_0.9.1 cluster_2.1.3
# [79] fs_1.5.2 magrittr_2.0.3 data.table_1.14.4
# [82] scattermore_0.8 SparseM_1.81 lmtest_0.9-40
# [85] RANN_2.6.1 truncnorm_1.0-8 SQUAREM_2021.1
# [88] fitdistrplus_1.1-8 matrixStats_0.62.0 pkgload_1.2.4
# [91] hms_1.1.1 patchwork_1.1.1 mime_0.12
# [94] evaluate_0.15 xtable_1.8-4 gridExtra_2.3
# [97] testthat_3.1.4 compiler_4.2.0 tibble_3.1.7
# [100] KernSmooth_2.23-20 crayon_1.5.1 R.oo_1.24.0
# [103] htmltools_0.5.2 later_1.3.0 tidyr_1.2.0
# [106] RcppParallel_5.1.5 DBI_1.1.2 MASS_7.3-56
# [109] rappdirs_0.3.3 Matrix_1.5-3 brio_1.1.3
# [112] cli_3.3.0 quadprog_1.5-8 R.methodsS3_1.8.1
# [115] parallel_4.2.0 igraph_1.3.1 pkgconfig_2.0.3
# [118] sp_1.6-0 plotly_4.10.0 spatstat.sparse_3.0-0
# [121] xml2_1.3.3 roxygen2_7.1.2 bslib_0.3.1
# [124] stringr_1.4.0 callr_3.7.0 digest_0.6.29
# [127] sctransform_0.3.5 RcppAnnoy_0.0.19 spatstat.data_3.0-0
# [130] leiden_0.3.10 uwot_0.1.14 shiny_1.7.1
# [133] quantreg_5.93 lifecycle_1.0.1 nlme_3.1-157
# [136] jsonlite_1.8.0 desc_1.4.1 viridisLite_0.4.0
# [139] fansi_1.0.3 pillar_1.7.0 lattice_0.20-45
# [142] fastmap_1.1.0 httr_1.4.2 pkgbuild_1.3.1
# [145] survival_3.3-1 glue_1.6.2 remotes_2.4.2
# [148] png_0.1-7 stringi_1.7.6 sass_0.4.1
# [151] memoise_2.0.1 dplyr_1.0.9 irlba_2.3.5
# [154] future.apply_1.9.0
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