Tool to computationally deconvolve combinatorially pooled arrayed random mutagenesis libraries
arraylib-solve is a tool to deconvolve combinatorially pooled arrayed random mutagenesis libraries (e.g. by transposon mutagenesis). In a typical experiment generating arrayed mutagenesis libraries, first a pooled version of the library is created and arrayed on a grid of well plates. To infer the identities of each mutant on the well plate, wells are pooled in combinatorial manner such that each mutant appears in a unique combination of pools. The pools are then sequenced using NGS and sequenced reads are stored in individual fastq files per pool.
arraylib-solve deconvolves the pools and returns summaries stating the identity and location of each mutant on the original well grid. The package is based on the approach described in .
arraylib first create
Python 3.8 environment e.g. by
conda create --name arraylib-env python=3.8
conda activate arraylib-env
and install the package using
pip install arraylib-solve
arraylib-solve uses bowtie2  to align reads to the reference genome. Please ensure that bowtie2 is installed in your environment by running:
conda install -c bioconda bowtie2
How to run
A detailed manual how to run
arraylib interactively and from the command line can be found here https://tcapraz.github.io/arraylib/index.html.
Baym, M., Shaket, L., Anzai, I.A., Adesina, O. and Barstow, B., 2016. Rapid construction of a whole-genome transposon insertion collection for Shewanella oneidensis by Knockout Sudoku. Nature communications, 7(1), p.13270.
 Langmead, B. and Salzberg, S.L., 2012. Fast gapped-read alignment with Bowtie 2. Nature methods, 9(4), pp.357-359.
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