initial commit

.gitignore

+.Rproj.user
+.Rhistory
+.RData
+.Ruserdata
+*fasta
+*fastq
+*csv
+*ods
+*txt
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README.md

 # swarm_and_obitools
 
+**Bastien Macé, 2020**
+
+## Introduction
+
 This project is based on the idea that gathering similar sequences allows to faithfully study them by elminating sequences generated from PCR or NGS errors.
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script_swarm_and_obitools.sh

+cd ## once you have conda installed, close the shell, reopen it and paste this 
+## following line :
+conda config --set auto_activate_base false
+
+########################################################################
+#STEP 1 : Create a new environment obitools
+
+ENVYAML=./dada2_and_obitools/obitools_env_conda.yaml
+conda env create -f $ENVYAML
+
+########################################################################
+#STEP 2 : Pair-end sequencing
+
+## unzip your data if you need :
+unzip mullus_surmuletus_data.zip
+
+## activate your environment :
+conda activate obitools
+
+## use the function illuminapairedend to make the pair-end sequencing from
+## the forward and reverse sequences you have in your data :
+illuminapairedend --score-min=40 -r mullus_surmuletus_data/200221_SN234_A_L001_AIMI-199_R1.fastq mullus_surmuletus_data/200221_SN234_A_L001_AIMI-199_R2.fastq > AIMI-199.fastq
+illuminapairedend --score-min=40 -r mullus_surmuletus_data/200221_SN234_A_L001_AIMI-200_R1.fastq mullus_surmuletus_data/200221_SN234_A_L001_AIMI-200_R2.fastq > AIMI-200.fastq
+
+## this function will create a new .fastq file which will contain the sequences
+## after the pair-end of forward and reverse sequences which have a quality 
+## score higher than 40 (-- score-min=40)
+
+## to only conserve the sequences which have been aligned, use obigrep :
+obigrep -p 'mode!="joined"' AIMI-199.fastq > AIMI-199.ali.fastq
+obigrep -p 'mode!="joined"' AIMI-200.fastq > AIMI-200.ali.fastq
+
+## -p requires a python expression
+
+## the unaligned sequences are notified with mode="joined" by illuminapairedend 
+## whereas the aligned sequences are notified with mode="aligned"
+
+## so here python creates new datasets (.ali.fastq) which only contain the
+## sequences notified "aligned"
+
+########################################################################
+#STEP 3 : Demultiplexing
+
+## to be able to compare the sequences next, you need to remove tags and primers,
+## and to use the function ngsfilter :
+ngsfilter -t mullus_surmuletus_data/AIMI_199_corr_tags.txt -u AIMI-199.unidentified.fastq AIMI-199.ali.fastq > AIMI-199.ali.assigned.fastq
+ngsfilter -t mullus_surmuletus_data/AIMI_200_corr_tags.txt -u AIMI-200.unidentified.fastq AIMI-200.ali.fastq > AIMI-200.ali.assigned.fastq
+
+## new files are created :
+## .unidentified.fastq files contain the sequences that were not assigned
+## whith a correct tag
+## .ali.assigned.fastq files contain the sequences that were assigned with
+## a correct tag, so it contains only the barcode sequences
+
+## separate your .ali.assigned.fastq files depending on their samples, 
+## in placing them in a  dedicated folder (useful for next steps) :
+mkdir samples
+
+## create the folder
+
+mv -t samples AIMI-199.ali.assigned.fastq AIMI-200.ali.assigned.fastq
+
+## place the latests .fastq files in the folder
+
+cd samples
+obisplit -t experiment --fastq AIMI-199.ali.assigned.fastq
+obisplit -t experiment --fastq AIMI-200.ali.assigned.fastq
+
+## separation of the files depending on their sample
+
+mv -t ./dada2_and_obitools AIMI-199.ali.assigned.fastq AIMI-200.ali.assigned.fastq
+
+## removing the original files from the folder
+
+obiuniq -m sample Aquarium_2.fastq > Aquarium_2.uniq.fasta
+obiannotate -k count -k merged_sample Aquarium_2.uniq.fasta > Aquarium_2.1.uniq.fasta 
+obigrep -l 20 -p 'count>=10' Aquarium_2.1.uniq.fasta > Aquarium_2.grep.fasta
+obiclean -s merged_sample -r 0.05 -H Aquarium_2.grep.fasta > Aquarium_2.clean.fasta
+obigrep -p 'obiclean_internalcount==0' Aquarium_2.clean.fasta > Aquarium_2.clean.grep.fasta
+obiannotate -k count Aquarium_2.clean.grep.fasta > Aquarium_2.1.clean.grep.fasta
+
+## la base de reference des individus rougets, et une base de données taxonomique du laboratoire rassemblant les especes de l’infra-classe Teleoste
+ecotag -m 0.5 -d /media/bmace/LaCie/projets/only_obitools/embl_std -R /media/bmace/LaCie/projets/only_obitools/base_ref_finale_formated.fasta Aquarium_2.1.clean.grep.fasta > Aquarium_2.tag.fasta
+obiannotate -k count Aquarium_2.tag.fasta > Aquarium_2.1.tag.fasta
+#bioedit
+
+obitab -o --output-field-separator=";" pipeline1_Aq2.fasta > pipeline1_Aq2.csv
+
+sumatra -t 1 pipeline1_Aq2.fasta /media/bmace/LaCie/projets/only_obitools/base_ref_finale_formated.fasta > pipeline1_Aq2.txt
+
+#modifier pipeline1_Aq2.fasta pour avoir le bon format pour swarm en pipeline1_Aq2.1.fasta
+swarm -z -d 0 -w pipeline1_Aq2.2.fasta -o /dev/null pipeline1_Aq2.1.fasta #si besoin de dérépliquer
+swarm -z -d 1 -f -t 10 -o stats_Aq2.txt -w pipeline3_Aq2.fasta < pipeline1_Aq2.2.fasta
+
+#modifier avec le filtrage d'Elbrecht
+sumatra -t 1 pipeline3_Aq2.fasta /media/bmace/LaCie/projets/swarm_and_obitools/base_ref_finale_formated.fasta > pipeline3_Aq2.txt
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swarm_and_obitools.Rproj

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+
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+Encoding: UTF-8
+
+RnwWeave: Sweave
+LaTeX: pdfLaTeX