DRB_TT-seq

Scripts for the analysis of TT-seq and DRB/TT-seq data.

This is a companion repository to the publication below.

Using TTchem-Seq to Profile Nascent Transcription and Measuring Transcript Elongation.
Lea H. Gregersen¹ Richard Mitter² and Jesper Q. Svejstrup¹.
¹Mechanisms of Transcription Laboratory, The Francis Crick Institute, 1 Midland Road, London, NW1 1AT, UK.
²Bioinformatics and Biostatistics, The Francis Crick Institute, 1 Midland Road, London NW1 1AT, UK.

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align.md

This is a bash markdown document for aligning paired Illumina sequence reads against a reference genome using STAR resulting in a sorted and indexed BAM file.

bigwig.md

This is a bash markdown document for generating scaled strand-specific BIGWIG files from a BAM file containing paired reads.

bigwig_bedtools.md

This is a bash markdown document for generating scaled strand-specific BIGWIG files from a BAM file containing paired reads. It is meant as an alternative to bigwig.md to be used on large bam files when deeptools struggles.

metaprofiles.md

This is a bash markdown document for generating strand-specific metagene, TSS and TES profiles from a BAM file using "ngs.plot".

DRB-TTseq.md

This is a markdown document describing a pipeline for calling RNA Pol II transcription wave peak positions and elongation rates from DRB/TT-seq time-series data using R. Instructions are given for calculating wave peaks at both the single-gene and meta-gene level. An Rmarkdown version of the scripts is available in the scripts An example html output of this script is given in DRB-TTseq.html - view raw, save to your desktop then open with your browser in order to view it. Users unfamiliar with R markdown are recommended to explore it using rstudio.

data

This directory contains details of demo FASTQ data available from the NCBI's Short Read Archive (SRA).

scripts

This directory contains plain script versions of the markdown documents.

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Dependencies and requirements

Scripts were tested using the following software versions:

• SAMtools v1.3.1
• deepTools v2.5.3
• BEDTools/2.27.1
• kentUtils
• STAR 2.5.2a
• Picard v2.1.1
• R v3.5.1 running Bioconductor version 3.7
• ngsplot v2.63

Example Bash scripts are written to be executed in a linux environment. Scripts were tested on a linux server equipped with a 8-core Intel E5-2640 Haswell CPU running at 2.6GHz and using 8 processors and 8gb RAM.

The R script may be run on any machine able to run R v3.5.1 or higher, though for large datasets it is recommended that at least 16gb RAM be made available to the process.

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References

• Andrews, S. FastQC: a quality control tool for high throughput sequence data. Available online at: http://www.bioinformatics.babraham.ac.uk/projects/fastqc (2010).

• Dobin, A. et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics 29, 15-21, doi:10.1093/bioinformatics/bts635 (2013).

• Hunt, S. E. et al. Ensembl variation resources. Database (Oxford) 2018, doi:10.1093/database/bay119 (2018).

• Kent WJ, Zweig AS, Barber G, Hinrichs AS, Karolchik D. BigWig and BigBed: enabling browsing of large distributed datasets. Bioinformatics. 2010 Sep 1;26(17):2204-7.

• Lawrence, M. et al. Software for computing and annotating genomic ranges. PLoS Comput Biol 9, e1003118, doi:10.1371/journal.pcbi.1003118 (2013).

• Li, H. et al. The Sequence Alignment/Map format and SAMtools. Bioinformatics 25, 2078-2079, doi:10.1093/bioinformatics/btp352 (2009).

• Mammana, A. H., J. bamsignals: Extract read count signals from bam files. R package version 1.12.11 (2016).

• Quinlan AR. BEDTools: The Swiss-Army Tool for Genome Feature Analysis. CurrProtoc Bioinformatics. 2014 Sep 8;47:11.12.1-34.

• Ramirez, F., Dundar, F., Diehl, S., Gruning, B. A. & Manke, T. deepTools: a flexible platform for exploring deep-sequencing data. Nucleic Acids Res 42, W187-191, doi:10.1093/nar/gku365 (2014).

• Shen, L., Shao, N., Liu, X. and Nestler, E. (2014) ngs.plot: Quick mining and visualization of next-generation sequencing data by integrating genomic databases, BMC Genomics, 15, 284.

• http://broadinstitute.github.io/picard/.