Project-2: SCEPTRE

<<<<<<< HEAD Last updated: 2022-08-04 ======= Last updated: 2022-07-19 >>>>>>> 37d15c9e90ebd440e24cbf0e45836e069685a838

Checks: 7 0

Knit directory: rotation2/

This reproducible R Markdown analysis was created with workflowr (version 1.7.0). The Checks tab describes the reproducibility checks that were applied when the results were created. The Past versions tab lists the development history.

R Markdown file: up-to-date

Great! Since the R Markdown file has been committed to the Git repository, you know the exact version of the code that produced these results.

Environment: empty

Great job! The global environment was empty. Objects defined in the global environment can affect the analysis in your R Markdown file in unknown ways. For reproduciblity it’s best to always run the code in an empty environment.

Seed: set.seed(20220607)

The command set.seed(20220607) was run prior to running the code in the R Markdown file. Setting a seed ensures that any results that rely on randomness, e.g. subsampling or permutations, are reproducible.

Session information: recorded

Great job! Recording the operating system, R version, and package versions is critical for reproducibility.

Cache: none

Nice! There were no cached chunks for this analysis, so you can be confident that you successfully produced the results during this run.

File paths: relative

Great job! Using relative paths to the files within your workflowr project makes it easier to run your code on other machines.

<<<<<<< HEAD Repository version: 3da8afa

Repository version: 3576593

>>>>>> 37d15c9e90ebd440e24cbf0e45836e069685a838 class="panel-collapse collapse">

Great! You are using Git for version control. Tracking code development and connecting the code version to the results is critical for reproducibility.

<<<<<<< HEAD The results in this page were generated with repository version 3da8afa. ======= The results in this page were generated with repository version 3576593. >>>>>>> 37d15c9e90ebd440e24cbf0e45836e069685a838 See the Past versions tab to see a history of the changes made to the R Markdown and HTML files.

Note that you need to be careful to ensure that all relevant files for the analysis have been committed to Git prior to generating the results (you can use wflow_publish or wflow_git_commit). workflowr only checks the R Markdown file, but you know if there are other scripts or data files that it depends on. Below is the status of the Git repository when the results were generated:


<<<<<<< HEAD
Unstaged changes:
    Modified:   .RData
    Modified:   .Rhistory
=======
Ignored files:
    Ignored:    data/
>>>>>>> 37d15c9e90ebd440e24cbf0e45836e069685a838

Note that any generated files, e.g. HTML, png, CSS, etc., are not included in this status report because it is ok for generated content to have uncommitted changes.

These are the previous versions of the repository in which changes were made to the R Markdown (analysis/project_2.Rmd) and HTML (docs/project_2.html) files. If you’ve configured a remote Git repository (see ?wflow_git_remote), click on the hyperlinks in the table below to view the files as they were in that past version.

File	Version	Author	Date	Message
<<<<<<< HEAD html	3da8afa	Hang Chen	2022-08-04	Build site.
html	37d15c9	chenh19	2022-07-19	Build site.
Rmd	3576593 ======= Rmd	3576593 >>>>>>> 37d15c9e90ebd440e24cbf0e45836e069685a838	chenh19	2022-07-19	wflow_publish("./analysis/*.Rmd")
html	<<<<<<< HEAD 8f6816e ======= 8f6816e >>>>>>> 37d15c9e90ebd440e24cbf0e45836e069685a838	chenh19	2022-07-19	Build site.
Rmd	<<<<<<< HEAD 383342f ======= 383342f >>>>>>> 37d15c9e90ebd440e24cbf0e45836e069685a838	chenh19	2022-07-19	wflow_publish("./analysis/*.Rmd")
html	<<<<<<< HEAD 4a94b94 ======= 4a94b94 >>>>>>> 37d15c9e90ebd440e24cbf0e45836e069685a838	chenh19	2022-07-19	Build site.
Rmd	<<<<<<< HEAD a18fc1f ======= a18fc1f >>>>>>> 37d15c9e90ebd440e24cbf0e45836e069685a838	chenh19	2022-07-19	wflow_publish("./analysis/*.Rmd")
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Rmd	<<<<<<< HEAD 8e0c8ad ======= 8e0c8ad >>>>>>> 37d15c9e90ebd440e24cbf0e45836e069685a838	chenh19	2022-06-21	wflow_publish("./analysis/*.Rmd")
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Rmd	<<<<<<< HEAD 49f1922 ======= 49f1922 >>>>>>> 37d15c9e90ebd440e24cbf0e45836e069685a838	chenh19	2022-06-14	wflow_publish("./analysis/*.Rmd")
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Rmd	<<<<<<< HEAD c43ae1f ======= c43ae1f >>>>>>> 37d15c9e90ebd440e24cbf0e45836e069685a838	chenh19	2022-06-13	wflow_publish("analysis/*.Rmd")
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1. Understand SCEPTRE

a. Read the paper

Barry et al. 2021: SCEPTRE

First, SCEPTRE fits a negative binomial distribution to measure the effect of a single gRNA on a given gene via Z-score. Then, the distribution of gRNAs to cells is randomly sampled to build a gRNA-specific null distribution, recomputing a negative binomial Z-score. A skew-t distribution is fit to compare the test Z-score and the null distribution, and a two-sided p-value is derived, allowing for significance tests of increased or decreased gene expression.

From Morris et al. 2021: STING-Seq

b. Check the package

c. Install the package

Code: sceptre.sh

d. run sceptre

SCEPTRE tutorial
SCEPTRE functions

Expression <- readRDS("../Morris_2021/filter/Expression.rds", refhook = NULL)
gRNA <- readRDS("../Morris_2021/filter/gRNA.rds", refhook = NULL)

gene_matrix <- Expression@assays$RNA@counts
gRNA_matrix <- gRNA@assays$RNA@counts

#install.packages("devtools")
#devtools::install_github("katsevich-lab/sceptre")
#install.packages("tidyverse")
#install.packages("cowplot")

library(tidyverse)
library(cowplot)
library(Matrix)
library(sceptre)

sessionInfo()

R version 4.2.1 (2022-06-23)
Platform: x86_64-pc-linux-gnu (64-bit)
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Running under: Ubuntu 22.04.1 LTS
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Running under: Ubuntu 22.04 LTS
>>>>>>> 37d15c9e90ebd440e24cbf0e45836e069685a838

Matrix products: default
BLAS:   /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.10.0
LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.10.0

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] workflowr_1.7.0

loaded via a namespace (and not attached):
<<<<<<< HEAD
 [1] Rcpp_1.0.9       compiler_4.2.1   pillar_1.8.0     bslib_0.4.0     
 [5] later_1.3.0      git2r_0.30.1     jquerylib_0.1.4  tools_4.2.1     
 [9] getPass_0.2-2    digest_0.6.29    jsonlite_1.8.0   evaluate_0.15   
[13] tibble_3.1.8     lifecycle_1.0.1  pkgconfig_2.0.3  rlang_1.0.4     
[17] cli_3.3.0        rstudioapi_0.13  yaml_2.3.5       xfun_0.31       
[21] fastmap_1.1.0    httr_1.4.3       stringr_1.4.0    knitr_1.39      
[25] fs_1.5.2         vctrs_0.4.1      sass_0.4.2       rprojroot_2.0.3 
[29] glue_1.6.2       R6_2.5.1         processx_3.7.0   fansi_1.0.3     
[33] rmarkdown_2.14   callr_3.7.1      magrittr_2.0.3   whisker_0.4     
[37] ps_1.7.1         promises_1.2.0.1 htmltools_0.5.3  httpuv_1.6.5    
[41] utf8_1.2.2       stringi_1.7.8    cachem_1.0.6

======= [1] Rcpp_1.0.9 compiler_4.2.1 pillar_1.8.0 bslib_0.3.1 [5] later_1.3.0 git2r_0.30.1 jquerylib_0.1.4 tools_4.2.1 [9] getPass_0.2-2 digest_0.6.29 jsonlite_1.8.0 evaluate_0.15 [13] tibble_3.1.7 lifecycle_1.0.1 pkgconfig_2.0.3 rlang_1.0.4 [17] cli_3.3.0 rstudioapi_0.13 yaml_2.3.5 xfun_0.31 [21] fastmap_1.1.0 httr_1.4.3 stringr_1.4.0 knitr_1.39 [25] sass_0.4.1 fs_1.5.2 vctrs_0.4.1 rprojroot_2.0.3 [29] glue_1.6.2 R6_2.5.1 processx_3.6.1 fansi_1.0.3 [33] rmarkdown_2.14 callr_3.7.0 magrittr_2.0.3 whisker_0.4 [37] ps_1.7.1 promises_1.2.0.1 htmltools_0.5.2 ellipsis_0.3.2 [41] httpuv_1.6.5 utf8_1.2.2 stringi_1.7.6 >>>>>>> 37d15c9e90ebd440e24cbf0e45836e069685a838