From 519832d9cbb13485bd4d5953a1309e02134fd4db Mon Sep 17 00:00:00 2001 From: Jonathan Robinson Date: Thu, 6 Aug 2020 11:38:35 +0200 Subject: [PATCH] remove old unused files --- envs/sylabs-token | 1 - reports/b_cell_purification.Rmd | 177 -------------------------------- 2 files changed, 178 deletions(-) delete mode 100644 envs/sylabs-token delete mode 100644 reports/b_cell_purification.Rmd diff --git a/envs/sylabs-token b/envs/sylabs-token deleted file mode 100644 index 0889f02..0000000 --- a/envs/sylabs-token +++ /dev/null @@ -1 +0,0 @@ -eyJhbGciOiJSUzI1NiIsInR5cCI6IkpXVCJ9.eyJleHAiOjE1ODY1MjMyNjEsImlhdCI6MTU4MzkzMTI2MSwiaXNzIjoiaHR0cHM6Ly9hdXRoLnN5bGFicy5pby90b2tlbiIsImp0aSI6IjVlNjhkZjdkNTJiN2I1NjMzZWFkOWJhMiIsInN1YiI6IjVkZDUxOGE1ZjFhM2YyZGUwNmFlYTE5NSJ9.fTmW1fZTX2OUDwzw8-UuxdhipsjIggGdimQvLaEknq_shRTNCkVd5FvrNoqx5lPTDr0rZvGzjdNaVtajWRjo-mhFB4-cDlcY-ibVaJSB_dRdHL2kHi0iq6Z5H1s_QsaflUaQSUuwAKuMiZkmJrDyl2T8945XwZAmMv3pUZriqfZHkIJaYSGF5pajjqUgn2C_dhU5Fyj1z-aZoaRkgSDNpSTXEB2CmMznQUXfyGelS4wpCO5LBft0PTN0oTacgJ7t6FcAiOTZS4a96dOAdjYcY4W3uyFTnJkcPlYNm_Mx6BD_anUrQAAhtPPm4Kz-l-bekyEu4JUdx9HQP7MqofZCig \ No newline at end of file diff --git a/reports/b_cell_purification.Rmd b/reports/b_cell_purification.Rmd deleted file mode 100644 index 422b1c8..0000000 --- a/reports/b_cell_purification.Rmd +++ /dev/null @@ -1,177 +0,0 @@ ---- -title: "Angeletti Data Analysis Report" -author: "Jonathan Robinson" -date: "`r Sys.Date()`" -output: - html_document: - fig_caption: yes - toc: no - pdf_document: - toc: yes -editor_options: - chunk_output_type: console ---- - - -```{r setup, include=FALSE} -knitr::opts_chunk$set(echo = F, results = 'hide', fig.width=8) -``` - -```{r} -# specify relevant directory information -pdir <- '/Users/jonrob/Documents/NBIS/LTS_projects/2020_DAngeletti/' # parent directiory -adir <- paste0(pdir,'analysis/') # analysis subdirectory -ddir <- paste0(pdir,'data/') # data subdirectory -``` - -```{r} -# load libraries and source functions -library(knitr) -# source('/Users/jonrob/Documents/NBIS/repos/niceRplots/R/plotting_functions.R') -``` - -# Purification of B-Cells {.tabset} - -## Pass 1 {.tabset} -```{r} -# specify parameters -cdir <- paste0(adir,'02_cluster/') -edir <- paste0(adir,'03_diff_expr/') -clust <- 'HC_12' -``` - -### Dimensionality reduction - -```{r, results='asis'} -metadata_fields <- c('organ','infection','day_post_infection') -for (mf in metadata_fields){ - cat('#### UMAP: colored by', unlist(strsplit(mf,'_'))) - cat('![](', cdir, 'umap_plots/umap_metadata_', mf, '.png', '){width=80%}\n', sep='') -} -``` - -### Clustering - -```{r, results='asis'} -cat('#### UMAP with mapped hierarchical cluster groups (', clust, ')', sep='') -cat('![](', paste0(cdir,'clustering/clustering_', clust, '_umap.png'), '){width=80%}', sep='') -``` - -### Differential expression - -#### Expression of top 3 DE genes per cluster -```{r, results='asis'} -cat('![](', paste0(edir,'violinPlot_genes_per_cluster_top3.png'), ')', sep='') -``` - -### Cell type prediction - -#### UMAP with mapped predicted (based on correlation) cell types for each cluster -```{r, results='asis'} -cat('![](', paste0(cdir,'cell_type_prediction/main_cell_types/cell_cluster_pred_correlation_umap.png'), '){width=80%}', sep='') -``` - -#### Table of cell-type specific genes used for prediction -```{r, results='asis'} -gene_table <- read.csv2(paste0(ddir,'cell_markers/main_cell_types.csv')) -kable(gene_table) -``` - - - -## Pass 2 {.tabset} -```{r} -# specify parameters -cdir <- paste0(adir,'04_cluster/') -edir <- paste0(adir,'05_diff_expr/') -clust <- 'HC_15' -``` - -### Dimensionality reduction - -```{r, results='asis'} -metadata_fields <- c('organ','infection','day_post_infection') -for (mf in metadata_fields){ - cat('#### UMAP: colored by', unlist(strsplit(mf,'_'))) - cat('![](', cdir, 'umap_plots/umap_metadata_', mf, '.png', '){width=80%}\n', sep='') -} -``` - -### Clustering - -```{r, results='asis'} -cat('#### UMAP with mapped hierarchical cluster groups (', clust, ')', sep='') -cat('![](', paste0(cdir,'clustering/clustering_', clust, '_umap.png'), '){width=80%}', sep='') -``` - -### Differential expression - -#### Expression of top 3 DE genes per cluster -```{r, results='asis'} -cat('![](', paste0(edir,'violinPlot_genes_per_cluster_top3.png'), ')', sep='') -``` - -### Cell type prediction - -#### UMAP with mapped predicted (based on correlation) cell types for each cluster -```{r, results='asis'} -cat('![](', paste0(cdir,'cell_type_prediction/main_cell_types/cell_cluster_pred_correlation_umap.png'), '){width=80%}', sep='') -``` - -#### Table of cell-type specific genes used for prediction -```{r, results='asis'} -gene_table <- read.csv2(paste0(ddir,'cell_markers/main_cell_types.csv')) -kable(gene_table) -``` - - - -## Pass 3 {.tabset} -```{r} -# specify parameters -cdir <- paste0(adir,'06_cluster/') -edir <- paste0(adir,'07_diff_expr/') -clust <- 'HC_11' -``` - -### Dimensionality reduction - -```{r, results='asis'} -metadata_fields <- c('organ','infection','day_post_infection') -for (mf in metadata_fields){ - cat('#### UMAP: colored by', unlist(strsplit(mf,'_'))) - cat('![](', cdir, 'umap_plots/umap_metadata_', mf, '.png', '){width=80%}\n', sep='') -} -``` - -### Clustering - -```{r, results='asis'} -cat('#### UMAP with mapped hierarchical cluster groups (', clust, ')', sep='') -# -cat('![](', paste0(cdir,'clustering/clustering_', clust, '_umap.png'), '){width=80%}', sep='') -``` - -### Differential expression - -#### Expression of top 3 DE genes per cluster -```{r, results='asis'} -cat('![](', paste0(edir,'violinPlot_genes_per_cluster_top3.png'), ')', sep='') -``` - -### Cell type prediction - -#### UMAP with mapped predicted (based on correlation) cell types for each cluster -```{r, results='asis'} -cat('![](', paste0(cdir,'cell_type_prediction/main_cell_types/cell_cluster_pred_correlation_umap.png'), '){width=80%}', sep='') -``` - -#### Table of cell-type specific genes used for prediction -```{r, results='asis'} -gene_table <- read.csv2(paste0(ddir,'cell_markers/main_cell_types.csv')) -kable(gene_table) -``` - - - -