Last updated: 2018-10-26

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ApiAP2 Activity Predictions

Here we will redo the analysis performed in Campbell et al. using motif hits within newly defined promoter regions. To perform this analysis, two R scripts need to be sourced from within the analysis working directory.

First generate_inputs.R, then estimate_apiap2_activity.R.

Bidirectional promoters

It would be interesting to see whether there is an enrichment for a particular motif found within bidirectional promoters. First let’s extract bidirectional promoter sequences:

Now create background files and run fimo:

And now we can read those files in and check the motif occurences:

Dynamic motif usage

Additionally, we can look at TSSs that we can confidentally say is shifting and analyze the motifs within these regions to find a nice example to display. We did this for KARHP:

Now we can look which motifs are unique to the short and long isoforms.

Session information

R version 3.5.0 (2018-04-23)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Gentoo/Linux

Matrix products: default
BLAS: /usr/local/lib64/R/lib/libRblas.so
LAPACK: /usr/local/lib64/R/lib/libRlapack.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] parallel  stats4    stats     graphics  grDevices utils     datasets 
[8] methods   base     

other attached packages:
 [1] gdtools_0.1.7                        
 [2] bindrcpp_0.2.2                       
 [3] BSgenome.Pfalciparum.PlasmoDB.v24_1.0
 [4] BSgenome_1.48.0                      
 [5] rtracklayer_1.40.6                   
 [6] Biostrings_2.48.0                    
 [7] XVector_0.20.0                       
 [8] GenomicRanges_1.32.7                 
 [9] GenomeInfoDb_1.16.0                  
[10] org.Pf.plasmo.db_3.6.0               
[11] AnnotationDbi_1.42.1                 
[12] IRanges_2.14.12                      
[13] S4Vectors_0.18.3                     
[14] Biobase_2.40.0                       
[15] BiocGenerics_0.26.0                  
[16] scales_1.0.0                         
[17] cowplot_0.9.3                        
[18] magrittr_1.5                         
[19] forcats_0.3.0                        
[20] stringr_1.3.1                        
[21] dplyr_0.7.6                          
[22] purrr_0.2.5                          
[23] readr_1.1.1                          
[24] tidyr_0.8.1                          
[25] tibble_1.4.2                         
[26] ggplot2_3.0.0                        
[27] tidyverse_1.2.1                      

loaded via a namespace (and not attached):
 [1] nlme_3.1-137                bitops_1.0-6               
 [3] matrixStats_0.54.0          lubridate_1.7.4            
 [5] bit64_0.9-7                 httr_1.3.1                 
 [7] rprojroot_1.3-2             tools_3.5.0                
 [9] backports_1.1.2             DT_0.4                     
[11] R6_2.3.0                    DBI_1.0.0                  
[13] lazyeval_0.2.1              colorspace_1.3-2           
[15] withr_2.1.2                 tidyselect_0.2.4           
[17] bit_1.1-14                  compiler_3.5.0             
[19] git2r_0.23.0                cli_1.0.1                  
[21] rvest_0.3.2                 xml2_1.2.0                 
[23] DelayedArray_0.6.6          labeling_0.3               
[25] digest_0.6.17               Rsamtools_1.32.3           
[27] svglite_1.2.1               rmarkdown_1.10             
[29] R.utils_2.7.0               pkgconfig_2.0.2            
[31] htmltools_0.3.6             htmlwidgets_1.3            
[33] rlang_0.2.2                 readxl_1.1.0               
[35] rstudioapi_0.8              RSQLite_2.1.1              
[37] shiny_1.1.0                 bindr_0.1.1                
[39] jsonlite_1.5                crosstalk_1.0.0            
[41] BiocParallel_1.14.2         R.oo_1.22.0                
[43] RCurl_1.95-4.11             GenomeInfoDbData_1.1.0     
[45] Matrix_1.2-14               Rcpp_0.12.19               
[47] munsell_0.5.0               R.methodsS3_1.7.1          
[49] stringi_1.2.4               whisker_0.3-2              
[51] yaml_2.2.0                  SummarizedExperiment_1.10.1
[53] zlibbioc_1.26.0             plyr_1.8.4                 
[55] grid_3.5.0                  blob_1.1.1                 
[57] promises_1.0.1              crayon_1.3.4               
[59] lattice_0.20-35             haven_1.1.2                
[61] hms_0.4.2                   knitr_1.20                 
[63] pillar_1.3.0                XML_3.98-1.16              
[65] glue_1.3.0                  evaluate_0.11              
[67] modelr_0.1.2                httpuv_1.4.5               
[69] cellranger_1.1.0            gtable_0.2.0               
[71] assertthat_0.2.0            mime_0.5                   
[73] xtable_1.8-3                broom_0.5.0                
[75] later_0.7.5                 GenomicAlignments_1.16.0   
[77] memoise_1.1.0               workflowr_1.1.1

This reproducible R Markdown analysis was created with workflowr 1.1.1