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README.md

aTRAM: automated Target Restricted Assembly Method Build Status

Background

aTRAM ("automated target restricted assembly method") is an iterative assembler that performs reference-guided local de novo assemblies using a variety of available methods. It is well-suited to various tasks where Next-Generation Sequence (NGS) data needs to be queried for gene sequences, such as phylogenomics. The design philosophy is modular and expandable, with support for four de-novo assemblers to date: Velvet, Abyss, Trinity, and Spades.

aTRAM 2 is a major overhaul of the aTRAM approach to assembling loci from (NGS) data. The new code has been reimplemented in Python, and the approach to short read library construction is completely revamped, resulting in major performance and assembly improvements.

Please consult the reference below for more information about aTRAM1.0: Allen, JM, DI Huang, QC Cronk, KP Johnson. 2015. aTRAM automated target restricted assembly method a fast method for assembling loci across divergent taxa from next-generation sequencing data. BMC Bioinformatics 16:98 DOI 10.1186/s12859-015-0515-2

The reference for aTRAM 2.0: Allen J.M., R. LaFrance, R. A. Folk, K. P. Johnson, and R. P. Guralnick In Press. aTRAM 2.0: An improved, flexible locus assembler for NGS data. Evolutionary Informatics

Installation

You will need to have Python3 installed, as well as pip, a package manager for Python.

git clone https://github.com/juliema/aTRAM.git
pip install --user --requirement atram/requirements.txt

aTRAM uses these programs so you need to install them.

You will need to use a locally installed BLAST:

You will also need at least one of the supported assembly modules:

If you want to use the atram stitcher you will need to install exonerate:

Installation using conda:

Alternatively, you can install both dependencies and aTRAM by using conda. Inside the aTRAM directory, run the following:

conda env create -f environment.yml
conda activate aTRAM

Quick start

Note: aTRAM 2 is not backwards compatible with aTRAM 1. It is also best to rebuild any libraries after major updates.

Library Preparation

Use atram_preprocessor.py for this.

  • Define your new library name with the --blast-db option. Which consists of a path and the library prefix itself. This program will add suffixes to differentiate different database files.

  • Then give it your fastq files. You can either list the forward and reverse read files, or put them into one file and use the --mixed-ends option.

Under the hood, aTRAM is building BLAST databases and an SQLite3 database for rapid read retrieval.

atram_preprocessor.py \
  --blast-db=path_to_atram_library/LIBRARY_PREFIX \
  --end-1=path_to_reads/read_1.fastq \
  --end-2=path_to_reads/read_2.fastq

Assembling Loci

atram.py uses the databases built by atram_preprocessor.py to assemble loci.

  • You need to give it the same --blast-db option from the preprocessor.
  • You also need to give it a query sequence. The query sequence is a FASTA file.
  • An assembler choice. The assembler choice is one of the assemblers mentioned above (velvet, trinity, abyss, or spades).
  • And an output prefix. The --output-prefix works just like the --blast-db-prefix with the directory part and the library prefix itself.
atram.py \
  --blast-db=path_to_atram_library/LIBRARY_PREFIX \
  --query=path_to_reference_loci/Locus.fasta \
  --assembler=ASSEMBLER_CHOICE \
  --output-prefix=path_to_output/OUTPUT_PREFIX

Stitching genes from assembled loci

atram_stitcher.py Takes the output assemblies from atram.py and reference amino acid targets and then stitches them together using an iterative process.

  • Give it a directory containing the assemblies.
  • A set of reference amino acid sequences in a FASTA file.
  • A list of taxon names. One taxon per line.
atram_stitcher.py \
  --assemblies-dir=path_to_assemblies \
  --reference-genes=path_to_genes/ref_genes.fasta \
  --taxa=path_to/taxon_list.txt

Documentation

Tutorials

Program Reference

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