BLISS_NatSciData

Code Repository for the BLISS Nature Scientific Data analyses

Getting Started

Required software

In order to succesfully execute the code in this repository, the following tools are needed:

• R >= 3.6.0
• R packages (available via Bioconductor):
  • AnnotationDbi
  • GenomicFeatures
  • rtracklayer
  • data.table
  • ggplot2
  • gridExtra
  • cowplot
  • scales
  • tximport
  • ChIPpeakAnno
  • ChIPseeker
  • org.Hs.eg.db
  • EnsDb.Hsapiens.v75
  • BSgenome.Hsapiens.UCSC.hg19
  • TxDb.Hsapiens.UCSC.hg19.knownGene
• Optional R packages (it would require you to change some parts of the code if not installed):
  • knitr
  • ggpubr
  • ggthemes
  • ggsci
  • viridis
  • RColorBrewer

Required actions

Some of the files that are employed in the script were too large to be uploaded without compression. As a result, they have to be decompressed before being read in R. You can do this by executing the following commands:

Move to the main folder

cd BLISS_NatSciData

Move the the RNA-seq folder and decompress salmon files

cd data/RNAseq
tar -zxvf salmon_quantification.tar.gz

Move the the Hi-C folder and decompress the pre-processed files

cd ../HiC
tar -zxvf eigenvector_data.tar.gz
tar -zxvf insulation_data.tar.gz
tar -zxvf loop_data.tar.gz

Finally, main script assumes that the suspension BLISS (sBLISS) BED files required are located in the data/BLISS folder. Moreover, you should either rename the BED files as shown below or change the corresponding names in the main script. The raw data can be downloaded from the Sequence Read Archive (SRA) under the accession PRJNA798046. For information on pre-processing, alignment and deduplication, please refer to the blissNP processing pipeline.

NES (replicate 1) --> NES_sBLISS_rep1.bed
NES (replicate 2) --> NES_sBLISS_rep2.bed
NPC (replicate 1) --> NPC_sBLISS_rep1.bed
NPC (replicate 2) --> NPC_sBLISS_rep2.bed
NEU (replicate 1) --> NEU_sBLISS_rep1.bed
NEU (replicate 2) --> NEU_sBLISS_rep2.bed

Once the data has been downloaded, processed and placed in the correct folder, you can open R and proceed with the analysis.