Last updated: 2022-03-07
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Knit directory: wildlife-ticks/
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| Rmd | 7b4fd7e | Siobhon Egan | 2022-03-07 | Update prj website |
Retrieve information for GenBank sequences used in the 12S rDNA phylogenetic analysis.
library(readxl)
df <- read_excel("data/12S_zotu_tree/MAFFT_aln_one_outgroup_refined_highlighted.xlsx")
View(df)library(ape)
ref <- df$GenBank
## Copy/paste or type the following commands if you
## want to try them.
# }
# NOT RUN {
Rampho <- read.GenBank(ref)
## get the species names:
attr(Rampho, "species")
## build a matrix with the species names and the accession numbers:
sp <- cbind(attr(Rampho, "species"), names(Rampho))
write.csv(sp, "data/12S_zotu_tree/speciesNames.csv")
## print the first sequence
## (can be done with `Rampho$U15717' as well)
Rampho[[1]]
## the description from each FASTA sequence:
attr(Rampho, "description")
# }source(../code/usearch11_12S_Ixodida.sh)# Enter raw data directorry
raw_data="raw_data"
# Enter raw read information on raw sequences
read_summary="1.read_sumary"
# Enter directory for merged output
merged_data="2.merged_data"
# Enter max diff for merging - default 5 but should increase for paired end
maxdiffs="15"
# Enter minimum merge overlap - default is 16 bp
overlap="20"
# Enter directory for sequences that are matched to primers
primer_matched="3a.primer_matches"
# Enter directory for sequences that do not match primers
primer_not_matched="3b.primer_not_matched"
# Enter forward sequences (5'-3'). Wildcard letters indicating degenerate positions in the primer are supported. See IUPAC(https://drive5.com/usearch/manual/IUPAC_codes.html) codes for details.
fwd_primer="AAACTAGGATTAGATACCCT" #12S Ixodida primer T1B, ref Beati and Keirans, J Parasitol (2001) 87(1):32-48
rev_primer="AATGAGAGCGACGGGCGATGT" #12S Ixodida primer T2A, ref Beati and Keirans, J Parasitol (2001) 87(1):32-48
# Enter directory for quality filtered output
QF="4.quality_filtered"
# Enter max error rate. Natural choice is 1, however may want to decrease to 0.5 or 0.25 for more stringent filtering.
max_ee="1"
# Enter min length of sequence for trimming in bp (eg. to keep all seqs above 200 bp enter "200")
minlen="150"
# Enter directory for labeled data
labeled_data="5.labeled_data"
# Enter directory for dereplicated sequences
derep_dir="6.derep_data"
# Enter directory for singlteton filter data
SF="7.singleton_filtered"
# Enter directory for singlteton sequences
low_abund_seqs="8.singleton_sequences"
# Enter max size to discard i.e. to discard singletons = 1, duplicates = 2
maxsize="1"
# Enter directory for sequence clustering
cluster="9.cluster"
# Enter sub-directory for uparse_otu clustering
uparse_otus="9a.otus"
# Enter sub-directory for unoise_zotu clustering
unoise_zotus="9b.zotus"
##########################################################################################
# DO NOT EDIT BELOW THIS LINE
##########################################################################################
##########################################################################################
gunzip ${raw_data}/*.fastq.gz
#echo %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
#echo Read summary of raw .fastq sequences
#echo %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
# Prouduce a short summary report of raw fastq sequences using `-fastx_info` command.
# Expected error should be <2 for both forward and reverse reads. Usually reverse reads have a higher error rate.
#mkdir $read_summary
#for fq in $raw_data/*R1*.fastq
# do
# echo ""
# echo ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# echo "fastq_info forward reads"
#
# usearch11.0.667_i86osx64 -fastx_info $fastq -output $read_summary/a_fwd_fastq_info.txt
#done
#for fq in $raw_data/*R2*.fastq
# do
# echo ""
# echo ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# echo "fastq_info forward reads"
# usearch11.0.667_i86osx64 -fastx_info $fastq -output $read_summary/b_rev_fastq_info.txt
#done
##########################################################################################
echo %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
echo Merging paried illumina .fastq sequences
echo %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
# Merge paired-end reads using `-fastq_mergepairs` command, and rename sequences. This would be done before primers are trimmed.
mkdir ${merged_data}
mkdir working1
#*****************************************************************************************
# Part 1: merge reads
for file1 in ${raw_data}/*R1.fastq
do
echo ""
echo ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
echo Merging paired reads
echo forward reads are:
echo $(basename ${file1})
echo reverse reads are:
echo $(basename ${file1} R1.fastq)R2.fastq
usearch11.0.667_i86osx64 -fastq_mergepairs ${file1} -reverse "${raw_data}/$(basename -s R1.fastq ${file1})R2.fastq" -fastqout "working1/$(basename "$file1")" -fastq_maxdiffs ${maxdiffs} -fastq_minovlen ${overlap} -report ${merged_data}/2a_merging_seqs_report.txt -tabbedout ${merged_data}/2b_tabbedout.txt
done
#*****************************************************************************************
# Part 2: Remove "_L001_R1_001" from filenames
for file2 in working1/*.fastq
do
rm -rfile2} _L001_R1.fastq).fastq"
mv ${file2} ${merged_data}/${rename}
done
#*****************************************************************************************
# Removing working directory
rm -r working1
##########################################################################################
echo %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
echo Triming primers and distal bases
echo %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
# The `-search_pcr2` command searches for matches to a primer pair and outputs the sequence in between (i.e. amplicon with primers removed) into `primer_matched` file
mkdir ${primer_matched}
mkdir ${primer_not_matched}
for file3 in ${merged_data}/*.fastq
do
usearch11.0.667_i86osx64 -search_pcr2 ${file3} -fwdprimer ${fwd_primer} \
-revprimer ${rev_primer} \
-strand both -fastqout "${primer_matched}/$(basename ${file3})" -notmatchedfq "${primer_not_matched}/$(basename ${file3})" -tabbedout ${primer_matched}pcr2_output.txt
done
##########################################################################################
echo %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
echo Quality control and removing dimer seqs
echo %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
# Quality filtering of fastq files using the `-fastq_filter` command, output gives fasta files.
mkdir ${QF}
for file4 in ${primer_matched}/*.fastq
do
echo ""
echo ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
echo Quality control and removing dimer seqs
echo input is:
echo ${file4}
usearch11.0.667_i86osx64 -fastq_filter ${file4} -fastaout "${QF}/$(basename "$file4" .fastq).fasta" -fastq_maxee ${max_ee} -fastq_minlen ${minlen}
done
##########################################################################################
echo %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
echo Renameing sequences with ">barcodelabel=sample_id;sequence_id"
echo %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
# For this script to run correctly input fasta label must be formatted >sequence_id and filename must be sample_id.fasta.
# Result will be ">barcodelabel=sample_id;sequenceid"
mkdir ${labeled_data}
mkdir working2
#*****************************************************************************************
# Part 1: Remove ">" from start of sequence_ID
for file5 in ${QF}/*.fasta
do
sed -e 's/>/>barcodelabel=;/g' ${file5} > working2/$(basename "$file5" .fasta).txt
done
#*****************************************************************************************
# Part 2: Add sample_ID (should be filename) to produce ">barcodelabel=sample_ID;sequence_ID"
for file6 in working2/*.txt
do
sample_id=$(basename ${file6} .txt)
echo ${sample_id}
sed -e "s/;/${sample_id};/g" ${file6} > "${labeled_data}/$(basename "$file6" .txt).fasta"
done
#*****************************************************************************************
# Remove working directories
rm -r working2
################################################################################################
echo %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
echo Removing low abundant seqs singletons per sample
echo %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
# Remove low abundant sequences (e.g. singletons) in samples using the `-fastx_uniques` command
mkdir ${derep_dir}
mkdir ${SF}
mkdir ${low_abund_seqs}
#*****************************************************************************************
# Part 1: Dereplicating
for file7 in ${labeled_data}/*.fasta
do
echo ""
echo ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
echo Removing singletons step 1: derep_fulllength
echo input is:
echo ${file7}
usearch11.0.667_i86osx64 -fastx_uniques ${file7} -fastaout "${derep_dir}/$(basename "$file7" .fasta).fasta" -sizeout
done
#*****************************************************************************************
# Part 2: Filtering low abundant seqs {maxsize}
for file8 in ${derep_dir}/*.fasta
do
echo ""
echo ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
echo Removing singletons step 2: sorting uniques
echo input is:
echo ${file8}
usearch11.0.667_i86osx64 -sortbysize ${file8} -fastaout "${low_abund_seqs}/$(basename "$file8" .fasta).fasta" -maxsize ${maxsize}
done
#*****************************************************************************************
# Step 3: Mapping reads
for file9 in ${labeled_data}/*.fasta
do
echo ""
echo ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
echo Removing singletons step 3: mapping reads to low abundant uniques
echo input is:
echo ${file9}
usearch11.0.667_i86osx64 -search_exact ${file9} -db "${low_abund_seqs}/$(basename "$file9" .fasta).fasta" -strand plus -notmatched "${SF}/$(basename "$file9" .fasta).fasta"
done
################################################################################################
################################################################################################
echo %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
echo CLUSTERING
echo %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
# Concatenate all singleton filter sequences into a single fasta file
# Find the set of unique sequences in an input file, also called dereplication using `-fastx_uniques` command
mkdir ${cluster}
cat ${SF}/*.fasta > ${cluster}/all_SF.fasta
cd ${cluster}
usearch11.0.667_i86osx64 -fastx_uniques all_SF.fasta -fastaout all_SF_DR.fasta -sizeout
#*****************************************************************************************
echo ----------------------------------------------------------------------------
echo Part a - Generating UPARSE OTUs
echo ----------------------------------------------------------------------------
# Cluster sequences in 97% operational taxonomic units (OTUs) using UPARSE algorithm `-cluster_otus` command and generate an OTU table
mkdir ${uparse_otus}
cd ${uparse_otus}
usearch11.0.667_i86osx64 -cluster_otus ../all_SF_DR.fasta -otus uparse_otus.fasta -relabel OTU
usearch11.0.667_i86osx64 -usearch_global ../all_SF.fasta -db uparse_otus.fasta -strand both -id 0.97 -otutabout uparse_otu_tab.txt -biomout uparse_otu_biom.biom
# The next two lines produce a distance matrix file and then a tree (newick format)
# Current parameters are a guide only and you will need to optimse them for your data
# Large datasets can take a long time, so you can skip this part for now to speed up analysis
# usearch11.0.667_i86osx64 -calc_distmx uparse_otus.fasta -tabbedout uparse_otus_distmx.txt -maxdist 0.2 -termdist 0.3
# usearch11.0.667_i86osx64 -cluster_aggd uparse_otus_distmx.txt -treeout uparse_otus_clusters.tree -clusterout uparse_otus_clusters.txt \
# -id 0.80 -linkage min
cd ..
#*****************************************************************************************
echo ----------------------------------------------------------------------------
echo Part b - Generating UNOISE ZOTUs
echo ----------------------------------------------------------------------------
# Cluster sequences in zero-radius operational taxonomic units (ZOTUs) using `-unoise3` command and generate a ZOTU table
mkdir ${unoise_zotus}
cd ${unoise_zotus}
usearch11.0.667_i86osx64 -unoise3 ../all_SF_DR.fasta -zotus unoise_zotus.fasta -tabbedout unoise_tab.txt
usearch11.0.667_i86osx64 -fastx_relabel unoise_zotus.fasta -prefix Otu -fastaout unoise_zotus_relabeled.fasta -keep_annots
usearch11.0.667_i86osx64 -otutab ../all_SF.fasta -zotus unoise_zotus_relabeled.fasta -otutabout unoise_otu_tab.txt -biomout unoise_otu_biom.biom -mapout unoise_map.txt -notmatched unoise_notmatched.fasta -dbmatched dbmatches.fasta -sizeout
# The next two lines produce a distance matrix file and then a tree (newick format)
# Current parameters are a guide only and you will need to optimse them for your data
# Large datasets can take a long time, so you can skip this part for now to speed up analysis
# usearch11.0.667_i86osx64 -calc_distmx unoise_zotus.fasta -tabbedout unoise_zotus_distmx.txt -maxdist 0.2 -termdist 0.3
# usearch11.0.667_i86osx64 -cluster_aggd unoise_zotus_distmx.txt -treeout unoise_zotus_clusters.tree -clusterout unoise_zotus_clusters.txt \
# -id 0.80 -linkage min
cd ..
cd ..
sessionInfo()