Content

1. Overview

2. Dependencies

3. Installation

4. Usage

5. Overview ===========

MetAssemble is a pipeline that runs several metagenomic assembly strategies combining Velvet, Meta-Velvet, Minimus2, Ray and Bambus2 on Illumina paired end reads. The pipeline was originally developed to validate the performance of the individual strategies, but can be used to perform the assembly strategies without validation as well. The pipeline is written in GNU make and not very user friendly for the average user, but if you are familiar with GNU make you shouldn't have too many troubles getting it to run. The only other metagenomics assembly pipeline that I am aware of is metAMOS, which seems to be an effort towards a more user-friendly approach if you are looking for that. A reason for using MetAssemble instead is because it allows one to schedule parts of the assembly pipeline with sbatch or qsub. Different steps in the assembly pipeline require different resources. Velvet for instance runs on only one node, whereas Ray runs over multiple. MetAssemble allows you to specify resource usage per rule with gnu-make-job-scheduler. Furthermore GNU make makes sure intermediate output files don't have to be recomputed in case of an error.

2. Dependencies =============== Dependencies need to be installed by oneself. There is no automated way to do this at the moment. One can however check if the dependencies are met by running

   bash test/dependencies/test_dependencies.sh

Do note that it is not necessary to install all programs if you only want to do a subset of the assemblies that MetAssemble covers. MetAssemble requires the following programs to perform all different assemblies:

Supported input:

• Illumina fastq CASAVA v1.8 paired end reads

Running the MetAssemble pipeline (scripts/Makefile) requires

• GNU make (tested on v3.81)

The Makefile features four steps of the metagenomic assembly pipeline:

1. Read processing.

   • Quality trimming
     • sickle

2. Assembling contigs

   • De Bruijn graph
     • Velvet 1.2.01
     • Meta-Velvet 1.2.01
     • Ray

3. Merging contigs

   • With cd-hit and minimus2. See Angus.
     • cd-hit-est NOTE: Increase MAX_SEQ when compiling. I put it at 3000000.
     • Minimus2 from Amos
     • MUMmer 3.23
   • Cut up contigs and merge with Newbler RunAssembly 2.6
     • scripts/process-reads/cut-up-fasta.py requires Biopython
     • Newbler RunAssembly 2.6 (COMMERCIAL)

4. Scaffolding

   • Construct linkage information by mapping reads to contigs
     • BWA
   • Scaffold contigs
     • Bambus2

5. Installation =============== After installing all the dependencies point METASSEMBLE_DIR environment variable to the root directory of this repository e.g.: export METASSEMBLE_DIR='~/gitrepos/metassemble'. You can do a test run with cd test && make test, which downloads a small set from the HMP project and runs a subset of all different assembly strategies in the MetAssemble pipeline.

6. Usage ======== See example in examples/chris-mock. There is a Makefile and a Makefile-sbatch which set some input paramaters and then include scripts/metassemble.mk and scripts/metassemble-scheduler.mk respectively. Hopefully that is clear enough to help you understand how to run your own subset of the available assembly strategies. If you want to change the resource usage per rule, change Makefile-sbatch accordingly. In the future I might add automatic computation of the resource usage. For assembly this is unfortunately still a problem, since it depends on the complexity of your sample and not just the filesize. The specified resource usage is for a library of ~1M and a mixed community of 60 bacteria and archaeae.

To see which assemblies have been created:

make echoexisting

All assemblies, created or not:

make echoall

To create all:

make all

Only show commands:

make -n all

Only make velvet:

make velvet

Schedule rules with sbatch:

make -f Makefile-sbatch all

For more rules check in the scripts/parameters.mk file.