tagMeppr

A computational pipeline to map TagMap-reads

TagMap is a very useful method for transposon mapping (Stern 2017), enabling researchers to map the insertion sites with ease and generate long sequencing reads. However, there is little to none automatisation and downstream analysis software available for these reads. TagMeppr is an easy to use, memory efficient fastq-to-figure package written in R.

Installation

# Install development version from GitHub
devtools::install_github("robinweide/tagmeppr")

The method

Find insertions

The findInsertions() function will first find all reads that overlap a TIS, which in the case of PiggyBac will be “TTAA”. Next it will calculate whether there is a bias towards one side of the TIS using a binominal test. The bias, denoted as , when all reads are upstream and when all reads are downstream of the TIS.This is done independently for the forward and reverse reads:

$\begin{aligned} p_{fwd/rev} = \binom{reads_{D<0}}{reads} \end{aligned}$

Next, we filter out TISs which have the bias on the same side of the TIS:

$\begin{aligned} sgn(D_{fwd}) \neq sgn(D_{rev}) \end{aligned}$

To calculate a “TIS-specific” p-value, we use Edgington’s sum-p method, which is very conservative in our usage. This ensures that, when $p_{combined} < \alpha$ , both the fwd and the rev reads are indeed biased.

$\begin{aligned} p_{combined} = \dfrac{(\sum_{i=1}^{2} p_i)^{2}}{2!} \end{aligned}$

Afterwards, a holm-correction is done to limit the Family-Wise Error Rate (FWER).

Usage

The basic usage of tagMapper revolves around three clear steps:

index: a tagMapper-index is made once for a specific genome and protocol (e.g. hg19 and PigyBac).
align: a tagMapperSample-object is made and aligned to the index
analyse: determine and plot highly likely integraton-sites

Within the analyse-step, you can choose to look at individually found insertion- sites with plotSite() to check the read-distribution. Here, reads from the forward and reverse primers overlapping the Target Insertion Site (TIS) are sorted. This can be helpfull for quality-checking and determining if the protocol behaves as expected. In the top-right corner is some important information about the selected hit: the two D-scores (denoting the bias of up- and downstream mapping of forward and reverse reads) and the probability.

You can also look at all found sites in one ideogram with plotInsertions(), subsetted on the orientation of the insertion and/or multiple samples.

See the vignette for a more in-depth coverage of all things tagMeppr!

BWA not found

Users with no root-access can install BWA themselves with bioconda or miniconda3. However, Rstudio will have troubles finding BWA. To fix this, run align() and makeIndex with the following:

library(withr)

with_path("/DATA/usr/r.weide/miniconda3/bin",
    {align(exp = mysample,
           ref = reference_mm10_TM,
           cores = 30)})

Code of conduct

Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms.

Stern, David L. 2017. “Tagmentation-Based Mapping (Tagmap) of Mobile Dna Genomic Insertion Sites.” bioRxiv. Cold Spring Harbor Laboratory. https://doi.org/10.1101/037762.

kuzmenkov111 / tagmeppr