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# Project_pbfb_Edisa_Xiu # Pipeline to analyze 16S rDNA sequences combining USEARCH and QIIME and community diversity analysis using R. #################################################################################################################### ##1 ##Obtain sequences from Dini-Andreote et al. 2014 The ISME Journal (30 samples in total: 2 months * 5 stages of succession * 3 replicates) ##The sequences are already merged and quality filtered in QIIME. (Sequences files : seqs.fna) (Information of the samples in MappingMJ1.txt) ##IMPORTANT: To check the sequence files just open the head in the cluster or the terminal. The size of the files are too big and your text editor may crash. #################################################################################################################### ##2 ##The original fna file has the following header: >1FMay_1 H23S4DR01B9UER orig_bc=CGTGTCTCTA new_bc=CGTGTCTCTA bc_diffs=0 ##and we need to change it into: >1FMay_1 sed 's/\s.*$//' seqs.fna > seqs.fa #################################################################################################################### ##3 ##Use USEARCH to pick OTU and make OTU table #You need to have the USEARCH software installed. #Write a script1.sh and run it in the Peregrine cluster sbatch script1.sh #!/bin/bash #SBATCH --job-name=project_EX #SBATCH --time=00:10:00 #SBATCH --nodes=1 #SBATCH --ntasks=4 #SBATCH --cpus-per-task=1 #SBATCH --mem=2G #SBATCH --partition=short pwd # Size annotation and remove singletons /data/miceco/software/usearch9.2.64_i86linux32 -fastx_uniques seqs.fa -fastaout uniques.fa -sizeout -relabel Uniq head uniques.fasta # Pick OTUs /data/miceco/software/usearch9.2.64_i86linux32 -cluster_otus uniques.fa -otus otus.fa -relabel OTU -minsize 2 head otus.fa grep -c "^>" otus.fa # Make OTU table /data/miceco/software/usearch9.2.64_i86linux32 -usearch_global seqs.fna -db otus.fa -strand plus -id 0.97 -otutabout otu_table.txt less –S otu_table.txt #################################################################################################################### ##4 # Using reorder_file.py to change the usearch format in "otu_table.txt" to QIIME format in order to use it in the pick representative OTU sequences step. ##to run the python script python reorder_file.py ##the reorder_file content: #!/usr/bin/env python filename = "otu_table.txt" outfile = "otu_table_reformatted.txt" out = file(outfile, "wb") with open(filename, "rb") as f: header = f.readline().split("\t") for line in f: splitline = line.split("\t") out.write(splitline[0]) for i in range(1,len(splitline)): if splitline[i] == "1": out.write("\t" + header[i]) out.write("\n") out.close() #Edit the header of "otu_table_reformatted.txt" (replace "OTU" to "denovo") cp otu_table_reformatted.txt seqs_otus.txt; sed -i -e 's/OTU/denovo/g' seqs_otus.txt ##5 #Edit the header of the output file from the pick otus step cp otus.fa otus_edited.fa; sed -i -e 's/>OTU/>denovo/g' otus_edited.fa #################################################################################################################### ##6 #Use QIIME to assign taxonomy and make OTU table with taxonomy #Write script 2 and run it in Peregrine cluster sbatch script2.sh #!/bin/bash #SBATCH --job-name=project_EX #SBATCH --time=00:30:00 #SBATCH --nodes=1 #SBATCH --ntasks=4 #SBATCH --cpus-per-task=1 #SBATCH --mem=2G #SBATCH --partition=short module load QIIME/1.9.1-foss-2016a-Python-2.7.11-tmp module list # Pick representative OTU sequences pick_rep_set.py -i seqs_otus.txt -f seqs.fa -o rep.fna # Assign_taxonomy assign_taxonomy.py -i rep_edited.fa -m uclust -o uclust_assigned_taxonomy -r 94_otus.fasta -t 94_otu_taxonomy.txt ####### Make_otu_table with taxonomy###### make_otu_table.py -i seqs_otus.txt -t uclust_assigned_taxonomy/rep_tax_assignments.txt -o otu_table1.biom # Remove singletons (Alternate step): filter_otus_from_otu_table.py -i otu_table1.biom -o otu_table2.biom -n 2 # Remove Unassigned filter_taxa_from_otu_table.py -i otu_table2.biom -n Unassigned -o otu_table.biom # convert to txt file with taxonomy: biom convert -i otu_table.biom -o OTUtable.from_biom_w_taxonomy.txt --header-key taxonomy --to-tsv #################################################################################################################### ##7 # Analyze microbial community diversity # The following steps run on R version 3.3.2 (2016-10-31) using RStudio interface # Install the libraries using Rpackages.R # Load the OTU table (OTUtable.from_biom_w_taxonomy.txt) to R and change the OTU table format using OTUtableformat.R # Change the header of OTUtable_nontaxon.txt using Header_mapping.csv in Microsoft Excel 2010 #################################################################################################################### ##8 # Calculate alpha diversity (Richness, shannon and simpson) and # draw the bar plot (Richness.png, Shannon.png and Simpson.png) using alpha_diversity.R #################################################################################################################### ##9 # Calculate beta diversity (bray-curtis) and make a plot (NMDS.png) using NMDS.R
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Project for the course pratical bioinformatic for biologist from Edisa and Xiu
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