TITLE: Sequencing and data quality control
AUTHORS: Adriana  Alberti, Julie Poulain, Stefan Engelen, Karine Labadie, Sarah Romac, Isabel Ferrera, Guillaume Albini, Jean-Marc Aury, Caroline Belser, Alexis Bertrand, Corinne Cruaud, Corinne Da Silva, Carole Dossat, Frédéric Gavory, Shahinaz Gas, Julie Guy, Maud Haquelle, E'krame Jacoby, Olivier Jaillon, Arnaud Lemainque, Eric Pelletier, Gaëlle Samson, Marc Wessner, Genoscope Technical Team, Silvia G. Acinas, Marta Royo-Llonch, Francisco M. Cornejo-Castillo, Ramiro Logares, Beatriz Fernández-Gómez, Chris Bowler, Guy Cochrane, Clara Amid, Petra Ten Hoopen, Colomban De Vargas, Nigel Grimsley, Elodie Desgranges, Stefanie Kandels-Lewis, Hiroyuki Ogata, Nicole Poulton, Michael E. Sieracki, Ramunas Stepanauskas, Matthew B. Sullivan, Jennifer R. Brum, Melissa B. Duhaime, Bonnie T. Poulos, Bonnie L. Hurwitz, Stéphane Pesant, Eric Karsenti, Patrick Wincker

[DESCRIPTION]
<div class = "text-blocks"><div class = "text-block"><span>This protocol describes the sequencing and data quality control for the </span><span style = "font-style:italic;">Tara</span><span> Oceans expedition and is part of </span><a href="https://www.protocols.io/view/viral-to-metazoan-marine-plankton-nucleotide-seque-qv6dw9e" style = "text-decoration:underline;color:blue;cursor:pointer;"><span style = ":;">Viral to metazoan marine plankton nucleotide sequences from the </span><span style = ":;font-style:italic;">Tara</span><span style = ":;"> Oceans expedition</span></a><span>. </span></div><div style = "text-align :; float : ;"><img style = "" src = "https://s3.amazonaws.com/pr-journal/3fueaie.jpg" /></div><div class = "text-block"><span style = "font-weight:bold;">Figure 3</span><span>: Overview of experimental pipeline from nucleic acids to sequences. (Red crosses highlight QC steps where experiments can be stopped.)</span></div></div>

[STEPS]
?. [Filtering]
Remove the sequences of the Illumina adapters and primers used during library construction from the whole reads. Remove low quality nucleotides with quality value
These trimming steps are achieved using fastx_clean (Code availability 3), a software based on the FASTX library (Code availability 4).
?. [Filtering]
Remove the reads and their mates that map onto run quality control sequences (Enterobacteria phage PhiX174 genome, Data Citation 1: GenBank NC_001422.1) using SOAP aligner.
?. [Filtering]
Apply a specific filter aiming to remove ribosomal reads to data generated from metatranscriptomic libraries sequencing. In Tara Oceans project, the reads and their mates that map onto a ribosomal sequences database are filtered using SortMeRNA v 1.0 (ref.), a biological sequence analysis tool for filtering, mapping and OTU-picking NGS reads. It contains different rRNA databases and we use it to split the data into two files: rRNA reads in a file (ribo_clean) and other reads in another file (noribo_clean).
?. [Data quality control]
Estimate duplicated sequences rates from single and paired sequences on raw reads and cleaned reads (after filtering steps), using fastx_estimate_duplicate (Code availability 5), a  software based on the FASTX library.
The following steps (4, 5 and 6) are performed on a subset of randomized 20,000 reads
?. [Data quality control]
Perform taxonomic assignation by aligning with Mega BLAST (Blast 2.2.15 suite) a subset of 20,000 reads against the nt database (http://www.ncbi.nlm.nih.gov/nucleotide), and using Megan software (version 3.9).
?. [Data quality control]
Do the merging step with fastx_mergepairs (Code availability 6), a software based on the fastx library. Extract the first 36 nucleotides of read2 and perform alignment between that seed and read1. Launch merging if the alignment was at least of 15 nucleotides, with less than 4 mismatches and an identity percent of at least 90%. For each overlapping position, retain the nucleotide of higher quality.
?. [Final data quality report ]
Calculate read size, quality values, N positions, base composition and  known adapters sequences detection before (raw reads) and after filtering the reads (cleaned reads). Evaluate each dataset using specific toolboxes generated from this pipeline (see Technical validation paragraph in paper).