README.md

In HIVDiversity/MotifBinner2: Processes NGS Primer ID Datasets

MotifBinner

MotifBinner processes high-throughput sequencing data of an RNA virus population that was sequenced using the Primer ID approach as described in Jabara et al, 2011. A random sequence tag is included in the initial primer during the conversion from RNA to cDNA so that each input template is tagged with a unique primer ID. After amplification with PCR and sequencing, each sequence with the same PID should be from the same input template.

This data is cleaned by scanning each sequence for a primer ID. A prefix and a suffix that surrounds the primer ID must be supplied. If the prefix and the suffix is found and the distance between them matches the primer ID length (supplied by user), then the letters between the prefix and suffix is taken as the primer ID for that sequence. Fuzzy matching is supported. All sequences with the same primer ID are then grouped together in bins so that each bin consists of sequences which had the same primer ID.

Bins that are made up of sequences whose primer IDs probably have sequencing errors in them are then discarded using the consensus cutoff approach (see the vignette on consensus cutoffs and Zhou et al, 2015 for more details). Each bin is then inspected and the most outlying sequences are removed so that the bins can be aligned without difficulty. The alignments are used to generate consensus sequences using a majority rule. The consensus sequences together with a report on the binning of the dataset is reported.

Installation Instructions for Ubuntu 14.04

Make sure you have a recent version of R: http://stackoverflow.com/questions/10476713/how-to-upgrade-r-in-ubuntu. Follow these instructions to set up the correct repositiory for apt.

Make sure that both r-base and r-base-dev is installed

sudo apt-get install r-base r-base-dev

Next, install devtools' depedancies and muscle using apt-get:

sudo apt-get install libssl-dev libxml2-dev libcurl4-gnutls-dev muscle

A very recent (at the time this README was written) version of pandoc is required: Download a binary package from https://github.com/jgm/pandoc/releases/1.15 and then install it with dpkg:

wget https://github.com/jgm/pandoc/releases/download/1.15/pandoc-1.15-1-amd64.deb
sudo dpkg -i pandoc-1.15-1-amd64.deb

Next install all the dependencies from Bioconductor. This is done from within an R session:

sudo R
source("http://bioconductor.org/biocLite.R")
biocLite("Biostrings")
biocLite("ShortRead")

Then, from within R, install devtools:

install.packages('devtools', repo = 'http://cran.rstudio.com/')

At last install MotifBinner: From a local file:

library(devtools)
install_local('/path/to/file/MotifBinner_x.y.z.tar.gz')

Please note that you must use install_local from devtools - install.packages will not work. Change /path/to/file to the path to the installation file on your computer and x.y.z to match the installation file you have.

Or using the bit_bucket repo:

library(devtools)
install_bitbucket('hivdiversity/MotifBinner2', 
  auth_user = 'username', password = 'password')

Lastly, MotifBinner includes a script that can be run from the commandline. You need to put this script somewhere convenient ('/usr/bin' for example)

file.symlink(from = file.path(find.package('MotifBinner2'), 'MotifBinner2.R'),
             to = '/usr/bin')

Usage

Within R

library(MotifBinner2)
help('process_file')

This will display the help for the main function in MotifBinner.

From the command line

MotifBinner2 -h

or (depending on your installation):

MotifBinner2.R -h

This will display help for all the options and an example call to MotifBinner.

Bibliography

• Cassandra B Jabara, Corbin D Jones, Jeffrey Roach, Jeffrey A Anderson, and Ronald Swanstrom. Accurate sampling and deep sequencing of the HIV- 1 protease gene using a Primer ID. Proceedings of the National Academy of Sciences of the United States of America, 108(50):20166–71, December 2011.

• Shuntai Zhou, Corbin Jones, Piotr Mieczkowski and Ronald Swanstrom. Primer ID validates template sampling depth and greatly reduced the error rate of next-generation sequencing of HIV1 genomic RNA populations. J Virol. 2015 Aug 15;89(16):8540-55. doi: 10.1128/JVI.00522-15. Epub 2015 Jun 3.

HIVDiversity/MotifBinner2 documentation built on May 6, 2019, 6:44 p.m.