MyNixOS website logo
Description

Analysis of COMRADES (Cross-Linking Matched RNA and Deep Sequencing) Data.

Analysis of RNA crosslinking data for RNA structure prediction. The package is suitable for the analysis of RNA structure cross-linking data and chemical probing data.

comradesOO

devtools::install_github("JLP-BioInf/comradesOO")

The COMRADES experiment


The COMRADES experimental protocol for the prediction of RNA structure in vivo was first published in 2018 (Ziv et al., 2019) where they predicted the structure of the Zika virus. The protocol has subsequently been use to predict the structure of SARS-CoV-2 (Ziv et al., 2020). Have a look to get an understanding of the protocol:

  • COMRADES determines in vivo RNA structures and interactions. (2018). Omer Ziv, Marta Gabryelska, Aaron Lun, Luca Gebert. Jessica Sheu-Gruttadauria and Luke Meredith, Zhong-Yu Liu, Chun Kit Kwok, Cheng-Feng Qin, Ian MacRae, Ian Goodfellow , John Marioni, Grzegorz Kudla, Eric Miska. Nature Methods. Volume 15. https://doi.org/10.1038/s41592-018-0121-0

  • The Short- and Long-Range RNA-RNA Interactome of SARS-CoV-2. (2020). Omer Ziv, Jonathan Price, Lyudmila Shalamova, Tsveta Kamenova, Ian Goodfellow, Friedemann Weber, Eric A. Miska. Molecular Cell, Volume 80 https://doi.org/10.1016/j.molcel.2020.11.004


Ziv et al., 2020. Virus-inoculated cells are crosslinked using clickable psoralen. Viral RNA is pulled down from the cell lysate using an array of biotinylated DNA probes, following digestion of the DNA probes and fragmentation of the RNA. Biotin is attached to crosslinked RNA duplexes via click chemistry, enabling pulling down crosslinked RNA using streptavidin beads. Half of the RNA duplexes are proximity-ligated, following reversal of the crosslinking to enable sequencing. The other half serves as a control, in which crosslink reversal proceeds the proximity ligation

After sequencing, short reads are produced similar to a spliced / chimeric RNA read but where one half of the read corresponds to one half of a structural RNA duplex and the other half of the reads corresponds to the other half of the structural RNA duplex. This package has been designed to analyse this data. The short reads need to be prepared in a specific way to be inputted into this package.

There are other types of crosslinking data!

PARIS


COMRADES data pre-processing

Nextflow pipeline


Fastq files produced from the comrades experiment can be processed for input into comradesOO using the Nextflow pre-processing pipeline, to get more information ---. The pipeline takes the reads through trimming alignment, QC and the production of the files necessary for input to comradesOO. Crosslinking experiments often have different library preparation protocols therefore it is not necessary to follow the prescribed pre-processing pipeline. The only requirement is that the input files for comradesOO have the correct format detailed below.

Nextflow pipeline output


The main output files are the files entitled X_gapped.txt. These are the input files for comradesOO. The columns of the output files are as follows:

  1. Read Name
  2. Read Sequence
  3. Side 1 transcript ID
  4. Side 1 Position start in read sequence
  5. Side 1 Position end in read sequence
  6. Side 1 Coordinate start in transcript
  7. Side 1 Coordinate end in transcript
  8. NA
  9. Side 2 transcript ID
  10. Side 2 Position start in read sequence
  11. Side 2 Position end in read sequence
  12. Side 2 Coordinate start in transcript
  13. Side 2 Coordinate end in transcript
  14. NA


Input for comrades-OO


The main input files for comrades-OO is a tab delimited text file containing the reads and mapping location on the transcriptome. This can be manually created if your library preparation protocol does not suit the pre-processing pipeline although the easiest way to obtain these files is to use the nextflow pipeline detailed above. There is test data that ships with the package, this contains data for the 18S rRNA and it's interactions with the 28S rRNA. However, full data-set already published can be found here:Un-enriched rRNA dataset.

Pre-requisites:

  1. Install the comradesOO package
  2. Input files (nexflow, custom or downloaded)
  3. Meta-data table
  4. ID of the RNA of interest (from the transcript reference )
  5. A fasta sequence of the RNA of interest (from the transcript reference )
  6. A set of interactions to compare to (optional)
  7. Reactivities (optional)
Metadata

Version

0.1.1

License

Unknown

Platforms (77)

    Darwin
    FreeBSD
    Genode
    GHCJS
    Linux
    MMIXware
    NetBSD
    none
    OpenBSD
    Redox
    Solaris
    WASI
    Windows
Show all
  • aarch64-darwin
  • aarch64-freebsd
  • aarch64-genode
  • aarch64-linux
  • aarch64-netbsd
  • aarch64-none
  • aarch64-windows
  • aarch64_be-none
  • arm-none
  • armv5tel-linux
  • armv6l-linux
  • armv6l-netbsd
  • armv6l-none
  • armv7a-darwin
  • armv7a-linux
  • armv7a-netbsd
  • armv7l-linux
  • armv7l-netbsd
  • avr-none
  • i686-cygwin
  • i686-darwin
  • i686-freebsd
  • i686-genode
  • i686-linux
  • i686-netbsd
  • i686-none
  • i686-openbsd
  • i686-windows
  • javascript-ghcjs
  • loongarch64-linux
  • m68k-linux
  • m68k-netbsd
  • m68k-none
  • microblaze-linux
  • microblaze-none
  • microblazeel-linux
  • microblazeel-none
  • mips-linux
  • mips-none
  • mips64-linux
  • mips64-none
  • mips64el-linux
  • mipsel-linux
  • mipsel-netbsd
  • mmix-mmixware
  • msp430-none
  • or1k-none
  • powerpc-netbsd
  • powerpc-none
  • powerpc64-linux
  • powerpc64le-linux
  • powerpcle-none
  • riscv32-linux
  • riscv32-netbsd
  • riscv32-none
  • riscv64-linux
  • riscv64-netbsd
  • riscv64-none
  • rx-none
  • s390-linux
  • s390-none
  • s390x-linux
  • s390x-none
  • vc4-none
  • wasm32-wasi
  • wasm64-wasi
  • x86_64-cygwin
  • x86_64-darwin
  • x86_64-freebsd
  • x86_64-genode
  • x86_64-linux
  • x86_64-netbsd
  • x86_64-none
  • x86_64-openbsd
  • x86_64-redox
  • x86_64-solaris
  • x86_64-windows