Login
Introduction Version

WGS with SqueezeMeta : no assembly


Introduction


Whole Genome Shotgun (WGS) metagenomic sequencing allows to sample all the genes of all the organisms present in a given complex sample. This method allows microbiologists to assess bacterial diversity and detect the abundance of microbes in various environments. WGS metagenomics also provides a means of studying non-cultivatable microorganisms that are otherwise difficult or impossible to analyse. 


This type of sequencing data can be used in a so-called (1) mapping analysis against a database of reference genes or (2) metagenomic assemblies followed by annotation of the assembled sequences and identification of the taxa present.



Data upload and preparation


Input fastq folder


One must upload one folder with all the sequencing data using the


. You must select the following format: Fastq folder.



Sample file


One must upload one file with all the information on the samples using the


. You must select the following format: File.


sample_file_list, expected format :
                          Sample1        readfileA_1.fastq       pair1
                          Sample1        readfileA_2.fastq      pair2
                          Sample1        readfileB_1.fastq       pair1
                          Sample1        readfileB_2.fastq      pair2
                          Sample3       readfileD_1.fastq       pair1       noassembly
                          Sample3       readfileD_2.fastq      pair2      noassembly


Protocol


Mapping reads



This task: gws_metag- Short Reads Mapping with SqueezeMeta performs taxonomic and functional assignment directly on the raw reads. The database used for the mapping is the nr Genbank database.


The first thing to choose is selecting the number of threads to run the analysis. One can put as much threads as available for the pipeline to take less time.


Another option is clustering_orthologous_groups. If set to true, it will perform a COG analysis (functional annotation) on the reads against the eggNOG database.


Files :