Overview

This pipeline output recapitulates a portion of the analysis described in D Mukherjee, et al. 2021. Egr2 induction in spiny projection neurons of the ventrolateral striatum contributes to cocaine place preference in mice. eLife 10:e65228 (PMID: 33724178)

RNA-sequencing analysis was performed on group in R. Analysis was carried out on the following contrasts: Acute_DS_1h-Acute_DS_0h, Acute_NAc_1h-Acute_NAc_0h, Acute_DS_0h-Acute_NAc_0h, Acute_DS_1h-Acute_NAc_1h, Acute_DSvNAc_1v0h=(Acute_DS_1h-Acute_DS_0h)-(Acute_NAc_1h-Acute_NAc_0h).

In all aspects of the study, false discovery rate (FDR) of 0.05 was considered significant, and in gene expression tests, absolute log2 fold change was required to be greater than 0.

The analysis proceeded in several stages outlined below. These included quality control of the data, multi-dimensional scaling analysis, and differential gene expression, which was performed using the edgeR package.

Quality control

37558 of 55367 genes were filtered out by requiring >1 CPM in at least 3 samples, leaving 17809 genes. Then 0 of 29 samples were filtered out based on total counts mapped to genes > 10000, leaving 29 samples.

Contains counts and related metadata

MDS plots

MDS analysis was performed on all samples in up to 30000 genes with respect to group.

MDS by group

Differential expression plots from LRT

Acute_DS_1h-Acute_DS_0h

Acute_NAc_1h-Acute_NAc_0h

Acute_DS_0h-Acute_NAc_0h

Acute_DS_1h-Acute_NAc_1h

Acute_DSvNAc_1v0h

Excel file contains differential expression results for each contrast and PDF contains accompanying plots

Differential expression results for each contrast may be found in accompanying Excel file out_group.top_tables.xlsx and accompanying plots in out_group.pdf.

Enrichment analysis

For all enrichment analyses, genes and categories were considered significant for FDR < 0.05. For list enrichment, genes were required to show absolute log2 fold change greater than 0. Where relevant, enrichment analyses were also carried out on gene rankings based on likelihood ratios signed in the same direction as log fold changes. Enrichment results were only retained if there were at least 3 genes supporting the enrichment. Gene Ontology list enrichment analysis was carried out using gene symbols from gene differential expression tables. KEGG pathway enrichment analysis was carried out using the species term mmu after conversion of gene symbols to NCBI gene IDs using the organism-specific R library org.Mm.eg.db.Analysis of the Molecular Signatures Database was carried out using the organism search string: mouse.Note that where list enrichment analyses involved fewer than 10 genes, the top 100 most significant gene symbols were analysed instead and further divided into up- and down-regulated gene lists. Up to 10 most significant enriched categories are shown in dot-plots below and accompanying pdf files with the prefix enr_, but full enrichment results, including genes constituting the enrichment, are found in accompanying Excel files with the prefix enr_. These may be found in the enrichment folder at this demo's GitHub repository.

Acute_DS_1h-Acute_DS_0h

GO

KEGG

C2

C5

H

Acute_NAc_1h-Acute_NAc_0h

GO

KEGG

C2

C5

H

Acute_DS_0h-Acute_NAc_0h

GO

KEGG

C2

C5

H

Acute_DS_1h-Acute_NAc_1h

GO

KEGG

C2

C5

H

Acute_DSvNAc_1v0h

GO

KEGG

C2

C5

H

100 overall most-significantly changed genes

Heatmap

Hierarchically Clustered

Contains hierarchically-clustered and metadata-clustered heatmaps of expression of top-100 differentially expressed genes

Clustered by Metadata

Contains hierarchically-clustered and metadata-clustered heatmaps of expression of top-100 differentially expressed genes

Bar-plots

Contains bar plots of expression of top-100 most-significantly differentially expressed genes

Library versions

## R version 4.5.0 (2025-04-11)
## Platform: x86_64-pc-linux-gnu
## Running under: Ubuntu 24.04.2 LTS
## 
## Matrix products: default
## BLAS:   /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.12.0 
## LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.12.0  LAPACK version 3.12.0
## 
## locale:
## [1] C
## 
## time zone: Europe/London
## tzcode source: system (glibc)
## 
## attached base packages:
## [1] stats4    stats     graphics  grDevices utils     datasets  methods  
## [8] base     
## 
## other attached packages:
##  [1] ggplotify_0.1.2        pheatmap_1.0.13        RColorBrewer_1.1-3    
##  [4] callr_3.7.6            retry_0.1.1            msigdbr_24.1.0        
##  [7] org.Mm.eg.db_3.21.0    AnnotationDbi_1.70.0   IRanges_2.42.0        
## [10] S4Vectors_0.46.0       Biobase_2.68.0         BiocGenerics_0.54.0   
## [13] generics_0.1.4         enrichplot_1.28.2      DOSE_4.2.0            
## [16] clusterProfiler_4.16.0 ggrastr_1.0.2          plotly_4.10.4         
## [19] openxlsx_4.2.8         lubridate_1.9.3        forcats_1.0.0         
## [22] stringr_1.5.1          dplyr_1.1.4            purrr_1.0.4           
## [25] readr_2.1.5            tidyr_1.3.1            tibble_3.3.0          
## [28] ggplot2_3.5.2          tidyverse_2.0.0        data.table_1.17.4     
## [31] edgeR_4.6.2            limma_3.64.1          
## 
## loaded via a namespace (and not attached):
##   [1] splines_4.5.0           filelock_1.0.3          R.oo_1.26.0            
##   [4] rpart_4.1.24            lifecycle_1.0.4         rstatix_0.7.2          
##   [7] processx_3.8.3          lattice_0.22-5          crosstalk_1.2.1        
##  [10] backports_1.5.0         magrittr_2.0.3          Hmisc_5.2-3            
##  [13] sass_0.4.10             rmarkdown_2.29          jquerylib_0.1.4        
##  [16] yaml_2.3.10             ggtangle_0.0.6          zip_2.3.1              
##  [19] cowplot_1.1.3           DBI_1.2.3               abind_1.4-8            
##  [22] R.utils_2.13.0          yulab.utils_0.2.0       nnet_7.3-20            
##  [25] rappdirs_0.3.3          GenomeInfoDbData_1.2.14 ggrepel_0.9.6          
##  [28] tidytree_0.4.6          codetools_0.2-20        tidyselect_1.2.1       
##  [31] aplot_0.2.6             UCSC.utils_1.4.0        farver_2.1.2           
##  [34] BiocFileCache_2.16.0    base64enc_0.1-3         jsonlite_2.0.0         
##  [37] Formula_1.2-5           systemfonts_1.2.3       tools_4.5.0            
##  [40] ragg_1.4.0              treeio_1.32.0           Rcpp_1.0.14            
##  [43] glue_1.8.0              gridExtra_2.3           xfun_0.52              
##  [46] qvalue_2.40.0           GenomeInfoDb_1.44.0     withr_3.0.2            
##  [49] BiocManager_1.30.26     fastmap_1.2.0           digest_0.6.37          
##  [52] timechange_0.3.0        R6_2.6.1                gridGraphics_0.5-1     
##  [55] textshaping_1.0.1       colorspace_2.1-1        GO.db_3.21.0           
##  [58] Cairo_1.6-2             dichromat_2.0-0.1       RSQLite_2.4.1          
##  [61] R.methodsS3_1.8.2       httr_1.4.7              htmlwidgets_1.6.4      
##  [64] pkgconfig_2.0.3         gtable_0.3.6            blob_1.2.4             
##  [67] XVector_0.48.0          htmltools_0.5.8.1       carData_3.0-5          
##  [70] fgsea_1.34.0            scales_1.4.0            png_0.1-8              
##  [73] ggfun_0.1.8             rstudioapi_0.17.1       knitr_1.50             
##  [76] tzdb_0.5.0              reshape2_1.4.4          checkmate_2.3.2        
##  [79] nlme_3.1-168            curl_6.3.0              cachem_1.1.0           
##  [82] BiocVersion_3.18.1      parallel_4.5.0          vipor_0.4.7            
##  [85] foreign_0.8-90          pillar_1.10.2           grid_4.5.0             
##  [88] vctrs_0.6.5             ggpubr_0.6.0            car_3.1-2              
##  [91] dbplyr_2.4.0            cluster_2.1.8.1         beeswarm_0.4.0         
##  [94] htmlTable_2.4.3         evaluate_1.0.3          cli_3.6.5              
##  [97] locfit_1.5-9.8          compiler_4.5.0          rlang_1.1.6            
## [100] crayon_1.5.3            ggsignif_0.6.4          labeling_0.4.3         
## [103] ps_1.7.6                plyr_1.8.9              fs_1.6.6               
## [106] ggbeeswarm_0.7.2        stringi_1.8.7           viridisLite_0.4.2      
## [109] BiocParallel_1.42.1     assertthat_0.2.1        babelgene_22.9         
## [112] Biostrings_2.76.0       lazyeval_0.2.2          GOSemSim_2.34.0        
## [115] Matrix_1.7-3            hms_1.1.3               patchwork_1.3.0        
## [118] bit64_4.6.0-1           KEGGREST_1.48.0         statmod_1.5.0          
## [121] AnnotationHub_3.16.0    igraph_2.1.4            broom_1.0.5            
## [124] memoise_2.0.1           bslib_0.9.0             ggtree_3.16.0          
## [127] fastmatch_1.1-6         bit_4.6.0               ape_5.8-1              
## [130] gson_0.1.0