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16S_pipeline.V9.sh
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16S_pipeline.V9.sh
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#/bin/sh -S
#########
#Please address any bugs to Cheng.
#Date 2018.9.13
#########
#echo $(readlink -f $1)
sample_metadata=$(readlink -f $1)
depth=$2
taxa_filtered="${3}"
category_sum=${4//,/ }
reference_trained=$(readlink -f $5)
close_reference_trained=$(readlink -f $6)
manifest_file=$(readlink -f $7)
not_rda=${8//\;/ }
classifier_type=$9
if_picrust=${10}
echo "Check wheather your categories are the following:"
for i in $category_sum;do echo $i;done
echo "Check wheather the group of enviromental factors excluded from rda are the following:"
for i in $not_rda;do echo $i;done
if [[ $if_picrust == 'yes' ]];then
echo "
Will run PICRUST"
else echo "
Won't run PICRUST"
fi
declare -A tax_aa;
tax_aa=([k]=Kingdom [p]=Phylum [c]=Class [o]=Order [f]=Family [g]=Genus [s]=Species);
tax_levels["1"]="Kingdom"
tax_levels["2"]="Phylum"
tax_levels["3"]="Class"
tax_levels["4"]="Order"
tax_levels["5"]="Family"
tax_levels["6"]="Genus"
tax_levels["7"]="Species"
#tax_levels1["k"]="Kingdom"
#tax_levels1["p"]="Phylum"
#tax_levels1["c"]="Class"
#tax_levels1["o"]="Order"
#tax_levels1["f"]="Family"
#tax_levels1["g"]="Genus"
#tax_levels1["s"]="Species"
if [ -z "$9" ]; then
echo "##########
Please prepare the directory structure before starting the program like below:
raw/fastq_files ...
mapping_file
manifest_file
\n\n"
echo "Please provide following input parameters
1) Path of the mapping file. (Accept both .csv or txt format.)
2) Depth of the for subsampleing. (Suggested value: 4000)
3) Taxa excluded from OTU table, seprated by commas.
4) The name of categories in the mapping file seprated by commas.
5) Path of the classifier for alignment.
6) Path of the reference sequences for close reference alignment.
7) Path of the manifest file.
8) Specify numeric variables excluded from rda seprated by commas,use 'none' if all numeric variables is expected. use 'all' to skip correlation analysis.
9) Specify the type of classifier, either silva or gg
10) wheather to run PICRUST, 'yes' or 'no'
Sample Usage:
bash ~/github/Bayegy/16S_pipeline.V9.sh ../data/sample-metadata.tsv auto 1000 Group ~/database_16S/GG/338-806/gg_13_8_99_338_806_classifier.qza ~/database_16S/GG/338-806/gg_13_5_97_338_806_ref_seqs.qza ../data/manifest.txt all gg yes
"
exit 0
else
echo "################
Running: sh $0 $1 $2 $3 $4 $5 $6 $7 $8 $9 ${10} "
fi
check_file() {
echo "Checking file for $1 ..."
file_name=$1
if [ -f $file_name ]; then
echo "File $file_name exists"
else
echo "File $file_name does not exist"
exit
fi
}
##Activate Qiime2 Version
echo "##############################################################\n#Initiate directory name and set up the directory structure"
SCRIPTPATH="$( cd "$(dirname "$0")" ; pwd -P )"
source $SCRIPTPATH/path/clean_path.sh
python3 $SCRIPTPATH/piputils/write_colors_plan.py -i $sample_metadata -c $4 -p $SCRIPTPATH/piputils/group_color.list -o colors_plan.json
if [ -f colors_plan.json ];then
source $SCRIPTPATH/piputils/put_colors_plan_path.sh $(readlink -f colors_plan.json)
echo "COLORS_PLAN_PATH = ${COLORS_PLAN_PATH}"
fi
source activate qiime2-2018.11
export TMPDIR='/home/admin1/TMPDIR'
echo "Classifier TMPDIR is ${TMPDIR}"
export JOBLIB_TEMP_FOLDER='/home/admin1/JOBLIB_TEMP_FOLDER'
echo "Classifier JOBLIB_TEMP_FOLDER is ${JOBLIB_TEMP_FOLDER}"
echo "##############################################################\n#paired end analysis using DADA2"
qiime tools import --type 'SampleData[PairedEndSequencesWithQuality]' --input-path $manifest_file --output-path demux.qza --input-format PairedEndFastqManifestPhred33
qiime demux summarize --i-data demux.qza --o-visualization demux.qzv
#qiime dada2 denoise-paired --i-demultiplexed-seqs demux.qza --p-trunc-len-f 290 --p-trunc-len-r 256 --p-trim-left-f 26 --p-trim-left-r 26 --o-representative-sequences rep-seqs-dada2.qza --o-table table-dada2.qza --p-n-threads 0 --o-denoising-stats stats-dada2.qza --verbose
#qiime dada2 denoise-paired --p-max-ee 100 --p-trunc-q 0 --i-demultiplexed-seqs demux.qza --p-trunc-len-f 290 --p-trunc-len-r 220 --p-trim-left-f 26 --p-trim-left-r 26 --o-representative-sequences rep-seqs-dada2.qza --o-table table-dada2.qza --p-n-threads 0 --o-denoising-stats stats-dada2.qza --verbose
qiime dada2 denoise-paired --i-demultiplexed-seqs demux.qza --p-trunc-len-f 290 --p-trunc-len-r 256 --p-trim-left-f 26 --p-trim-left-r 26 --o-representative-sequences rep-seqs-dada2.qza --o-table table-dada2.qza --p-n-threads 0 --o-denoising-stats stats-dada2.qza --verbose
#qiime dada2 denoise-paired --i-demultiplexed-seqs demux.qza --p-trunc-len-f 290 --p-trunc-len-r 220 --p-trim-left-f 26 --p-trim-left-r 26 --o-representative-sequences rep-seqs-dada2.qza --o-table table-dada2.qza --p-n-threads 0 --o-denoising-stats stats-dada2.qza --verbose
qiime metadata tabulate --m-input-file stats-dada2.qza --o-visualization stats-dada2.qzv
<<comment2
echo "##############################################################\n#Single end analysis using DADA2"
qiime tools import --type 'SampleData[SequencesWithQuality]' --input-path $manifest_file --output-path demux.qza --input-format SingleEndFastqManifestPhred33
qiime demux summarize --i-data demux.qza --o-visualization demux.qzv
qiime dada2 denoise-single --i-demultiplexed-seqs demux.qza --p-max-ee 50 --p-trunc-q 0 --p-trunc-len 240 --p-trim-left 0 --o-representative-sequences rep-seqs-dada2.qza --o-table table-dada2.qza --p-n-threads 0 --o-denoising-stats stats-dada2.qza --verbose
qiime metadata tabulate --m-input-file stats-dada2.qza --o-visualization stats-dada2.qzv
comment2
<<comment1
echo "############################################################\nAlternative methods of read-joining using deblur"
qiime tools import --type 'SampleData[PairedEndSequencesWithQuality]' --input-path $manifest_file --output-path demux.qza --input-format PairedEndFastqManifestPhred33
#qiime cutadapt trim-paired --i-demultiplexed-sequences demux.qza --p-front-f CCAGCASCYGCGGTAATTCC --p-front-r ACTTTCGTTCTTGATYRA --p-overlap 10 --o-trimmed-sequences trimmed-demux.qza
#qiime tools import --type 'SampleData[JoinedSequencesWithQuality]' --input-path $manifest_file --output-path demux-joined.qza --input-format SingleEndFastqManifestPhred33
qiime vsearch join-pairs --p-maxdiffs 5 --p-minovlen 15 --p-truncqual 2 --i-demultiplexed-seqs demux.qza --o-joined-sequences demux-joined.qza
qiime demux summarize --i-data demux-joined.qza --o-visualization demux.qzv
qiime quality-filter q-score-joined --i-demux demux-joined.qza --o-filtered-sequences demux-joined-filtered.qza --o-filter-stats demux-joined-filter-stats.qza
qiime deblur denoise-16S --i-demultiplexed-seqs demux-joined-filtered.qza --p-trim-length 400 --p-sample-stats --o-representative-sequences rep-seqs-dada2.qza --o-table table-dada2.qza --o-stats stats-dada2.qza --p-jobs-to-start 16 --verbose
qiime deblur visualize-stats --i-deblur-stats stats-dada2.qza --o-visualization stats-dada2.qzv
comment1
mv rep-seqs-dada2.qza rep-seqs.withCandM.qza
mv table-dada2.qza table.withCandM.qza
# Output the OTUid_frequency-talbe txt file, this file is the raw talbe, without any filtering.
echo "qiime tools export --input-path table.withCandM.qza --output-path table.withCandM.without_filtering"
qiime tools export --input-path table.withCandM.qza --output-path table.withCandM.without_filtering
echo "biom convert --to-tsv -i table.withCandM.without_filtering/feature-table.biom -o table.withCandM.without_filtering/feature-table.tsv"
biom convert --to-tsv -i table.withCandM.without_filtering/feature-table.biom -o table.withCandM.without_filtering/feature-table.tsv
echo "##############################################################\n#Classify the taxonomy"
check_file $reference_trained
qiime feature-classifier classify-sklearn --verbose --p-confidence 0.7 --p-n-jobs 1 --i-classifier $reference_trained --i-reads rep-seqs.withCandM.qza --o-classification taxonomy.withCandM.qza
# qiime feature-classifier classify-sklearn --verbose --p-confidence 0.55 --p-n-jobs 1 --i-classifier $reference_trained --i-query rep-seqs.withCandM.qza --o-classification taxonomy.withCandM.qza
#qiime feature-classifier classify-consensus-vsearch --i-query rep-seqs.withCandM.qza --i-reference-reads ~/database_ITS/UNITE_release/full-length/rep-set.qza --i-reference-taxonomy ~/database_ITS/UNITE_release/full-length/ref-taxonomy.qza --p-perc-identity 0.7 --o-classification taxonomy.withCandM.qza
qiime metadata tabulate --m-input-file taxonomy.withCandM.qza --o-visualization taxonomy.withCandM.qzv
# Output the OTUid_taxonomy txt file, without filtering the mitochondria,chloroplast,Unassigned
echo "qiime tools export --input-path taxonomy.withCandM.qza --output-path taxonomy.withCandM.without_filtering"
qiime tools export --input-path taxonomy.withCandM.qza --output-path taxonomy.withCandM.without_filtering
#Archaea,
# qiime taxa filter-table --i-table table.withCandM.qza --i-taxonomy taxonomy.withCandM.qza --p-exclude ${taxa_filtered}mitochondria,chloroplast,Unassigned --o-filtered-table table-no-mitochondria-no-chloroplast.qza
# mv table-no-mitochondria-no-chloroplast.qza table.qza
# qiime taxa filter-seqs --i-sequences rep-seqs.withCandM.qza --i-taxonomy taxonomy.withCandM.qza --p-exclude ${taxa_filtered}mitochondria,chloroplast,Unassigned --o-filtered-sequences rep-seqs-no-mitochondria-no-chloroplast.qza
# mv rep-seqs-no-mitochondria-no-chloroplast.qza rep-seqs.qza
# qiime feature-classifier classify-sklearn --verbose --p-confidence 0.4 --p-n-jobs 1 --i-classifier $reference_trained --i-reads rep-seqs.qza --o-classification taxonomy.qza
echo "Filter parameter is ${taxa_filtered}"
filter_source.py -i table.withCandM.qza -r rep-seqs.withCandM.qza -t taxonomy.withCandM.qza -f "${taxa_filtered}"
if [[ $classifier_type == 'silva' ]];
then python $SCRIPTPATH/format_silva_to_gg.py -i taxonomy.qza;
else python $SCRIPTPATH/format_silva_to_gg.py -i taxonomy.qza -c;
fi;
echo "##############################################################\n#Generate tree";
qiime alignment mafft --i-sequences rep-seqs.qza --o-alignment aligned-rep-seqs.qza
qiime alignment mask --i-alignment aligned-rep-seqs.qza --o-masked-alignment masked-aligned-rep-seqs.qza
qiime phylogeny fasttree --i-alignment masked-aligned-rep-seqs.qza --o-tree unrooted-tree.qza
qiime phylogeny midpoint-root --i-tree unrooted-tree.qza --o-rooted-tree rooted-tree.qza
qiime feature-table tabulate-seqs --i-data rep-seqs.qza --o-visualization rep-seqs.qzv
echo "##############################################################\n#Generate OTUStats";
for f in rep-seqs.qza table.qza taxonomy.qza ; do echo $f; qiime tools export --input-path $f --output-path exported; done
#for f in alpha-rarefaction.qzv table.qzv taxa-bar-plots.qzv; do echo $f; qiime tools export --input-path $f --output-path exported_qzv; done
qiime tools export --input-path rooted-tree.qza --output-path exported/
mv exported/tree.nwk exported/tree.rooted.nwk
qiime tools export --input-path unrooted-tree.qza --output-path exported/
mv exported/tree.nwk exported/tree.unrooted.nwk
biom add-metadata -i exported/feature-table.biom -o exported/feature-table.taxonomy.biom --observation-metadata-fp exported/taxonomy.tsv --observation-header OTUID,taxonomy,confidence
biom convert -i exported/feature-table.taxonomy.biom -o exported/feature-table.taxonomy.txt --to-tsv --header-key taxonomy
for f in $(find . -type f -name "*.qzv"); do echo $f; base=$(basename $f .qzv); dir=$(dirname $f); new=${dir}/${base}; qiime tools export --input-path $f --output-path ${new}.qzv.exported; done
source deactivate
source activate qm2
echo "##############################################################\n#Generate the figure for the percentage of annotated level"
perl ${SCRIPTPATH}/stat_otu_tab.unspecifiedadded.pl -unif min exported/feature-table.taxonomy.txt -prefix exported/Relative/otu_table --even exported/Relative/otu_table.even.txt -spestat exported/Relative/classified_stat_relative.xls > /dev/null
perl ${SCRIPTPATH}/bar_diagram.pl -table exported/Relative/classified_stat_relative.xls -style 1 -x_title "Sample Name" -y_title "Sequence Number Percent" -right -textup -rotate='-45' --y_mun 1,7 > exported/Relative/Classified_stat_relative.svg
for svg_file in exported/Relative/*svg; do echo $svg_file; n=$(basename "$svg_file" .svg); echo $n; rsvg-convert -h 3200 -b white $svg_file > exported/Relative/${n}.png; done
if [ -d "./Result" ];then
rm -r ./Result;
fi;
mkdir -p ./Result/1-OTUStats/3-RepresentiveSequence/;
cp -r demux.qzv* stats-dada2.qzv* ./Result/1-OTUStats/
cp -r ./rep-seqs.qzv* ./exported/*nwk ./exported/dna-sequences.fasta ./Result/1-OTUStats/3-RepresentiveSequence/
for f in $(find ./Result/1-OTUStats/ -type f -name "*qzv"); do echo $f; base=$(basename $f .qzv); dir=$(dirname $f); mv $f ${f}.exported; mv ${f}.exported ${dir}/${base}; done
for f in $(find ./Result/1-OTUStats/ -type f -name "index.html") ; do echo $f; base=$(basename $f .html); dir=$(dirname $f); new=${dir}/Summary_请点此文件查看.html; mv $f $new; done
mv ./Result/1-OTUStats/stats-dada2 ./Result/1-OTUStats/2-Stats-dada2
mv ./Result/1-OTUStats/demux/ ./Result/1-OTUStats/1-Stats-demux
cp -r exported/feature-table.taxonomy.txt exported/feature-table.taxonomy.biom exported/Relative/Classified_stat_relative.png exported/Relative/classified_stat_relative.xls ./Result/1-OTUStats/
cp -r exported/Relative/otu_table.even.txt ./Result/1-OTUStats/feature-table.taxonomy.even.txt
echo "##############################################################\n#Generate the results of each group"
for category_set in $category_sum;
do echo $category_set;
source deactivate;
source activate qiime2-2018.11;
#mkdir ${category_set}_Results;
python $SCRIPTPATH/filter_source.py -i table.qza -t taxonomy.qza -r rep-seqs.qza -m $sample_metadata -c $category_set -o ${category_set}_Results;
cd ${category_set}_Results;
mapping_file=$(readlink -f './mapping_file.txt');
qiime metadata tabulate --m-input-file taxonomy.qza --o-visualization taxonomy.qzv;
echo "##############################################################\n#Generate tree";
qiime alignment mafft --i-sequences rep-seqs.qza --o-alignment aligned-rep-seqs.qza
qiime alignment mask --i-alignment aligned-rep-seqs.qza --o-masked-alignment masked-aligned-rep-seqs.qza
qiime phylogeny fasttree --i-alignment masked-aligned-rep-seqs.qza --o-tree unrooted-tree.qza
qiime phylogeny midpoint-root --i-tree unrooted-tree.qza --o-rooted-tree rooted-tree.qza
echo "##############################################################\n#Visulize of the table without Choloroplast and Mitochondira"
qiime feature-table summarize --i-table table.qza --o-visualization table.qzv --m-sample-metadata-file $mapping_file
qiime taxa barplot --i-table table.qza --i-taxonomy taxonomy.qza --m-metadata-file $mapping_file --o-visualization taxa-bar-plots.qzv
#########calculate the min sample depth
#for f in rep-seqs.qza table.qza taxonomy.qza ; do echo $f; qiime tools export --input-path $f --output-path exported; done
qiime tools export --input-path table.qzv --output-path exported_qzv
if [[ $depth == 'auto' ]];
then min_depth=$(echo \($(cut -f2 -d ',' exported_qzv/sample-frequency-detail.csv | sort -n | head -n1)/1000\)*1000 | bc);
else min_depth=$depth;
fi;
echo "##############################################################The selected sample depth is $min_depth"
echo "##############################################################\n#Core alpha and beta diversity analysis"
qiime diversity core-metrics-phylogenetic --i-phylogeny rooted-tree.qza --i-table table.qza --p-sampling-depth $min_depth --m-metadata-file $mapping_file --output-dir core-metrics-results
#qiime diversity alpha-group-significance --i-alpha-diversity core-metrics-results/faith_pd_vector.qza --m-metadata-file $mapping_file --o-visualization core-metrics-results/faith-pd-group-significance.qzv
#qiime diversity alpha-group-significance --i-alpha-diversity core-metrics-results/evenness_vector.qza --m-metadata-file $mapping_file --o-visualization core-metrics-results/evenness-group-significance.qzv
#qiime diversity alpha-group-significance --i-alpha-diversity core-metrics-results/shannon_vector.qza --m-metadata-file $mapping_file --o-visualization core-metrics-results/shannon-group-significance.qzv
#qiime diversity alpha-group-significance --i-alpha-diversity core-metrics-results/observed_otus_vector.qza --m-metadata-file $mapping_file --o-visualization core-metrics-results/observed_otus-group-significance.qzv
for category_1 in $category_set;
do echo $category_1;
qiime diversity beta-group-significance --i-distance-matrix core-metrics-results/unweighted_unifrac_distance_matrix.qza --m-metadata-file $mapping_file --p-method permanova --m-metadata-column $category_1 --o-visualization 'core-metrics-results/unweighted_unifrac-permanova-'$category_1'-significance.qzv' --p-pairwise;
#qiime diversity beta-group-significance --i-distance-matrix core-metrics-results/unweighted_unifrac_distance_matrix.qza --m-metadata-file $mapping_file --p-method permanova --m-metadata-column $category_2 --o-visualization 'core-metrics-results/unweighted_unifrac-permanova-'$category_2'-significance.qzv' --p-pairwise
qiime diversity beta-group-significance --i-distance-matrix core-metrics-results/weighted_unifrac_distance_matrix.qza --m-metadata-file $mapping_file --p-method permanova --m-metadata-column $category_1 --o-visualization 'core-metrics-results/weighted_unifrac-permanova-'$category_1'-significance.qzv' --p-pairwise;
#qiime diversity beta-group-significance --i-distance-matrix core-metrics-results/weighted_unifrac_distance_matrix.qza --m-metadata-file $mapping_file --p-method permanova --m-metadata-column $category_2 --o-visualization 'core-metrics-results/weighted_unifrac-permanova-'$category_2'-significance.qzv' --p-pairwise
qiime diversity beta-group-significance --i-distance-matrix core-metrics-results/bray_curtis_distance_matrix.qza --m-metadata-file $mapping_file --p-method permanova --m-metadata-column $category_1 --o-visualization 'core-metrics-results/bray_curtis-permanova-'$category_1'-significance.qzv' --p-pairwise;
#qiime diversity beta-group-significance --i-distance-matrix core-metrics-results/bray_curtis_distance_matrix.qza --m-metadata-file $mapping_file --p-method permanova --m-metadata-column $category_2 --o-visualization 'core-metrics-results/bray_curtis-permanova-'$category_2'-significance.qzv' --p-pairwise
qiime diversity beta-group-significance --i-distance-matrix core-metrics-results/unweighted_unifrac_distance_matrix.qza --m-metadata-file $mapping_file --p-method anosim --m-metadata-column $category_1 --o-visualization 'core-metrics-results/unweighted_unifrac-anosim-'$category_1'-significance.qzv' --p-pairwise;
#qiime diversity beta-group-significance --i-distance-matrix core-metrics-results/unweighted_unifrac_distance_matrix.qza --m-metadata-file $mapping_file --p-method anosim --m-metadata-column $category_2 --o-visualization 'core-metrics-results/unweighted_unifrac-anosim-'$category_2'-significance.qzv' --p-pairwise
qiime diversity beta-group-significance --i-distance-matrix core-metrics-results/weighted_unifrac_distance_matrix.qza --m-metadata-file $mapping_file --p-method anosim --m-metadata-column $category_1 --o-visualization 'core-metrics-results/weighted_unifrac-anosim-'$category_1'-significance.qzv' --p-pairwise;
#qiime diversity beta-group-significance --i-distance-matrix core-metrics-results/weighted_unifrac_distance_matrix.qza --m-metadata-file $mapping_file --p-method anosim --m-metadata-column $category_2 --o-visualization 'core-metrics-results/weighted_unifrac-anosim-'$category_2'-significance.qzv' --p-pairwise
qiime diversity beta-group-significance --i-distance-matrix core-metrics-results/bray_curtis_distance_matrix.qza --m-metadata-file $mapping_file --p-method anosim --m-metadata-column $category_1 --o-visualization 'core-metrics-results/bray_curtis-anosim-'$category_1'-significance.qzv' --p-pairwise;
done;
#qiime diversity beta-group-significance --i-distance-matrix core-metrics-results/bray_curtis_distance_matrix.qza --m-metadata-file $mapping_file --p-method anosim --m-metadata-column $category_2 --o-visualization 'core-metrics-results/bray_curtis-anosim-'$category_2'-significance.qzv' --p-pairwise
qiime diversity alpha-rarefaction --i-table table.qza --i-phylogeny rooted-tree.qza --p-max-depth $min_depth --m-metadata-file $mapping_file --o-visualization alpha-rarefaction.qzv --p-steps 50
##These following two commands work only for column with numeric values:
##qiime emperor plot --i-pcoa core-metrics-results/unweighted_unifrac_pcoa_results.qza --m-metadata-file $mapping_file --p-custom-axis $category_2 --o-visualization 'core-metrics-results/unweighted_unifrac-emperor-'$category_2'.qzv'
##qiime emperor plot --i-pcoa core-metrics-results/bray_curtis_pcoa_results.qza --m-metadata-file $mapping_file --p-custom-axis $category_2 --o-visualization 'core-metrics-results/bray-curtis-emperor-'$category_2'.qzv'
echo "##############################################################\n#alpha dviersity summary"
mkdir alpha alpha_groupsignificance
#qiime diversity alpha --i-table table.qza --p-metric chao1 --output-dir alpha/chao1
#qiime diversity alpha --i-table table.qza --p-metric shannon --output-dir alpha/shannon
#qiime diversity alpha --i-table table.qza --p-metric observed_otus --output-dir alpha/observed_otus
qiime diversity alpha-phylogenetic --i-table table.qza --i-phylogeny rooted-tree.qza --p-metric faith_pd --output-dir alpha/faith_pd
#qiime diversity alpha --i-table table.qza --p-metric simpson --o-alpha-diversity alpha/simpson.qza
#qiime diversity alpha --i-table table.qza --p-metric ace --o-alpha-diversity alpha/ace.qza
#qiime diversity alpha --i-table table.qza --p-metric goods_coverage --o-alpha-diversity alpha/goods_coverage.qza
for alpha_index in chao1 shannon observed_otus faith_pd simpson;
do echo $alpha_index;
if [ ! $alpha_index == faith_pd ];then
qiime diversity alpha --i-table table.qza --p-metric ${alpha_index} --output-dir alpha/${alpha_index}/
fi;
qiime tools export --input-path alpha/${alpha_index}/alpha_diversity.qza --output-path alpha/${alpha_index}/;
#if [ ! $alpha_index == goods_coverage ];then
qiime diversity alpha-group-significance --i-alpha-diversity alpha/${alpha_index}/alpha_diversity.qza --m-metadata-file $mapping_file --o-visualization alpha_groupsignificance/${alpha_index}-group-significance.qzv;
#fi;
done;
#qiime tools export --input-path alpha/chao1/alpha_diversity.qza --output-path alpha/chao1/
#qiime tools export --input-path alpha/shannon/alpha_diversity.qza --output-path alpha/shannon/
#qiime tools export --input-path alpha/observed_otus/alpha_diversity.qza --output-path alpha/observed_otus/
#qiime tools export --input-path alpha/faith_pd/alpha_diversity.qza --output-path alpha/faith_pd/
#qiime tools export --input-path alpha/simpson.qza --output-path alpha/simpson/
#qiime tools export --input-path alpha/ace.qza --output-path alpha/ace/
#qiime tools export --input-path alpha/goods_coverage.qza --output-path alpha/goods_coverage/
#paste alpha/observed_otus/alpha-diversity.tsv alpha/chao1/alpha-diversity.tsv alpha/shannon/alpha-diversity.tsv alpha/faith_pd/alpha-diversity.tsv alpha/simpson/alpha-diversity.tsv alpha/ace/alpha-diversity.tsv alpha/goods_coverage/alpha-diversity.tsv | awk -F'\t' 'BEGIN{OFS="\t"}{print $1, $2, $4, $6, $8, $10, $12, $14}' > alpha/alpha-summary.tsv
paste alpha/observed_otus/alpha-diversity.tsv alpha/chao1/alpha-diversity.tsv alpha/shannon/alpha-diversity.tsv alpha/faith_pd/alpha-diversity.tsv alpha/simpson/alpha-diversity.tsv | awk -F'\t' 'BEGIN{OFS="\t"}{print $1, $2, $4, $6, $8, $10}' > alpha/alpha-summary.tsv
echo "##############################################################\n#Export necessary files for future analysis"
for f in rep-seqs.qza table.qza taxonomy.qza ; do echo $f; qiime tools export --input-path $f --output-path exported; done
#for f in alpha-rarefaction.qzv table.qzv taxa-bar-plots.qzv; do echo $f; qiime tools export --input-path $f --output-path exported_qzv; done
qiime tools export --input-path rooted-tree.qza --output-path exported/
mv exported/tree.nwk exported/tree.rooted.nwk
qiime tools export --input-path unrooted-tree.qza --output-path exported/
mv exported/tree.nwk exported/tree.unrooted.nwk
biom add-metadata -i exported/feature-table.biom -o exported/feature-table.taxonomy.biom --observation-metadata-fp exported/taxonomy.tsv --observation-header OTUID,taxonomy,confidence
biom convert -i exported/feature-table.taxonomy.biom -o exported/feature-table.taxonomy.txt --to-tsv --header-key taxonomy
biom convert -i exported/feature-table.taxonomy.biom -o exported/feature-table.txt --to-tsv
echo "##############################################################\n#Generate heatmaps for top OTUs with different levels with minimum frequence reads supported"
mkdir exported/collapsed
# mkdir exported/${min_freq}
for n in 2 3 4 5 6 7;
do echo $n;
qiime taxa collapse --i-table table.qza --i-taxonomy taxonomy.qza --p-level $n --o-collapsed-table exported/collapsed/collapsed-${tax_levels[${n}]}.qza;
qiime feature-table summarize --i-table exported/collapsed/collapsed-${tax_levels[${n}]}.qza --o-visualization exported/collapsed/collapsed-${tax_levels[${n}]}.qzv '--m-sample-metadata-file' $mapping_file;
# qiime feature-table filter-features --i-table exported/collapsed/collapsed-${tax_levels[${n}]}.qza --p-min-frequency $min_freq --o-filtered-table exported/${min_freq}/table-${tax_levels[${n}]}.${min_freq}.qza;
<<COMMENT
for category_1 in $category_set;
do echo $category_1;
Rscript ${SCRIPTPATH}/clean_na_of_inputs.R -m $mapping_file --group $category_1 -t exported/${min_freq}/table-${tax_levels[${n}]}.${min_freq}.qza -o media_files
qiime feature-table heatmap --i-table media_files/filtered_feature_table.qza --m-metadata-file media_files/cleaned_map.txt --m-metadata-column $category_1 --o-visualization exported/${min_freq}/${category_1}-table-${tax_levels[${n}]}.${min_freq}.qzv;
done;
COMMENT
done;
source deactivate
source activate qm2
echo "##############################################################\n#Generate the figure for the percentage of annotated level"
perl ${SCRIPTPATH}/stat_otu_tab.unspecifiedadded.pl -unif min exported/feature-table.taxonomy.txt -prefix exported/Relative/otu_table --even exported/Relative/otu_table.even.txt -spestat exported/Relative/classified_stat_relative.xls
perl ${SCRIPTPATH}/bar_diagram.pl -table exported/Relative/classified_stat_relative.xls -style 1 -x_title "Sample Name" -y_title "Sequence Number Percent" -right -textup -rotate='-45' --y_mun 1,7 > exported/Relative/Classified_stat_relative.svg
# Rscript ${SCRIPTPATH}/taxonomy_stats.R -i exported/feature-table.ConsensusLineage.txt -o TaxaStatistic
sed 's/taxonomy/Consensus Lineage/' < exported/feature-table.taxonomy.txt | sed 's/ConsensusLineage/Consensus Lineage/' > exported/feature-table.ConsensusLineage-raw.txt
sed 's/taxonomy/Consensus Lineage/' < exported/Relative/otu_table.even.txt | sed 's/ConsensusLineage/Consensus Lineage/' > exported/feature-table.ConsensusLineage.txt
sed -i '1i\# Constructed from biom file' exported/feature-table.ConsensusLineage.txt
Rscript ${SCRIPTPATH}/taxonomy_stats.R -i exported/feature-table.ConsensusLineage-raw.txt -o TaxaStatistic
Rscript ${SCRIPTPATH}/collapse_table_with_group_mean.R -m $mapping_file -c $category_set -t exported/Relative/classified_stat_relative.xls -o ./
perl ${SCRIPTPATH}/bar_diagram.pl -table ${category_set}_classified_stat_relative.xls -style 1 -x_title "" -y_title "Sequence Number Percent" -right -textup -rotate='-45' --y_mun 1,7 > ${category_set}_classified_stat_relative.svg
for svg_file in *svg; do echo $svg_file; n=$(basename "$svg_file" .svg); echo $n; rsvg-convert -h 3200 -b white $svg_file > ${n}.png; done
for key in ${!tax_aa[*]};do mv exported/Relative/otu_table.${key}.relative.mat exported/Relative/otu_table.${tax_aa[$key]}.relative.txt;done;
#mv exported/Relative/otu_table.p.relative.mat exported/Relative/otu_table.Phylum.relative.txt
#mv exported/Relative/otu_table.c.relative.mat exported/Relative/otu_table.Class.relative.txt
#mv exported/Relative/otu_table.o.relative.mat exported/Relative/otu_table.Order.relative.txt
#mv exported/Relative/otu_table.f.relative.mat exported/Relative/otu_table.Family.relative.txt
#mv exported/Relative/otu_table.g.relative.mat exported/Relative/otu_table.Genus.relative.txt
#mv exported/Relative/otu_table.s.relative.mat exported/Relative/otu_table.Species.relative.txt
# for n7 in "Phylum" "Class" "Order" "Family" "Genus" "Species";
# do echo $n7;
#echo "mv exported/Relative/otu_table.${n7}.relative.mat exported/Relative/otu_table.${tax_levels[${n7}]}.relative.txt"
#mv exported/Relative/otu_table.${n7}.relative.mat exported/Relative/otu_table.${tax_levels[${n7}]}.relative.txt
#echo ${tax_levels[$n7]}
#echo ${tax_levels[${n7}]}
# perl -lane '$,="\t";pop(@F);print(@F)' exported/Relative/otu_table.${n7}.relative.txt > exported/Relative/otu_table.${n7}.relative.lastcolumn.txt;
# perl ${SCRIPTPATH}/get_table_head2.pl exported/Relative/otu_table.${n7}.relative.lastcolumn.txt 20 -trantab > exported/Relative/otu_table.${n7}.relative.lastcolumn.trans;
#perl ${SCRIPTPATH}/bar_diagram.pl -table exported/Relative/otu_table.${n7}.relative.lastcolumn.trans -style 1 -x_title "Sample Name" -y_title "Sequence Number Percent" -right -textup -rotate='-45' --y_mun 1,1 > exported/Relative/otu_table.${n7}.relative.svg;
# perl ${SCRIPTPATH}/bar_diagram.pl -table exported/Relative/otu_table.${n7}.relative.lastcolumn.trans -style 1 -x_title "Sample Name" -y_title "Sequence Number Percent (%)" -right -textup -rotate='-45' --y_mun 0.2,5 --micro_scale --percentage > exported/Relative/otu_table.${n7}.relative.svg
# done;
for svg_file in exported/Relative/*svg; do echo $svg_file; n=$(basename "$svg_file" .svg); echo $n; rsvg-convert -h 3200 -b white $svg_file > exported/Relative/${n}.png; done
source deactivate
source activate qiime2-2018.11
echo "ANCOM analaysis for differential OTU"
mkdir exported/ANCOM
for n2 in 2 3 4 5 6 7;
do echo $n2;
for category_1 in $category_set;
do echo $category_1;
Rscript ${SCRIPTPATH}/clean_na_of_inputs.R -m $mapping_file --group $category_1 -t exported/collapsed/collapsed-${tax_levels[${n2}]}.qza -o media_files
qiime composition add-pseudocount --i-table media_files/filtered_feature_table.qza --o-composition-table exported/ANCOM/composition.${tax_levels[${n2}]}.qza;
qiime composition ancom --i-table exported/ANCOM/composition.${tax_levels[${n2}]}.qza --m-metadata-file media_files/cleaned_map.txt --m-metadata-column $category_1 --o-visualization exported/ANCOM/${category_1}.ANCOM.${tax_levels[${n2}]}.qzv;
done;
#qiime composition ancom --i-table exported/ANCOM/composition.${tax_levels[${n2}]}.qza --m-metadata-file $mapping_file --m-metadata-column $category_2 --o-visualization exported/ANCOM/SecondaryGroup/ANCOM.${tax_levels[${n2}]}.qzv;
done;
if [[ $if_picrust == 'yes' ]];then
echo "##############################################################\n#Run for PICRUST analysis and STAMP visulization";
qiime vsearch cluster-features-closed-reference --i-sequences rep-seqs.qza --i-table table.qza --i-reference-sequences $close_reference_trained --p-perc-identity 0.97 --p-threads 0 --output-dir closedRef_forPICRUSt
qiime feature-table summarize --i-table closedRef_forPICRUSt/clustered_table.qza --o-visualization closedRef_forPICRUSt/clustered_table.qzv --m-sample-metadata-file $mapping_file
qiime feature-table tabulate-seqs --i-data closedRef_forPICRUSt/unmatched_sequences.qza --o-visualization closedRef_forPICRUSt/unmatched_sequences.qzv
qiime tools export --input-path closedRef_forPICRUSt/clustered_table.qza --output-path closedRef_forPICRUSt/
biom convert -i closedRef_forPICRUSt/feature-table.biom -o closedRef_forPICRUSt/feature-table.txt --to-tsv
export PYTHONPATH=/home/admin1/miniconda3/lib/python2.7/site-packages/
normalize_by_copy_number.py -i closedRef_forPICRUSt/feature-table.biom -o closedRef_forPICRUSt/feature-table.normalized.biom
predict_metagenomes.py -i closedRef_forPICRUSt/feature-table.normalized.biom -o closedRef_forPICRUSt/feature-table.metagenome.biom
categorize_by_function.py -i closedRef_forPICRUSt/feature-table.metagenome.biom -o closedRef_forPICRUSt/feature-table.metagenome.L1.txt -c KEGG_Pathways -l 1 -f
categorize_by_function.py -i closedRef_forPICRUSt/feature-table.metagenome.biom -o closedRef_forPICRUSt/feature-table.metagenome.L2.txt -c KEGG_Pathways -l 2 -f
categorize_by_function.py -i closedRef_forPICRUSt/feature-table.metagenome.biom -o closedRef_forPICRUSt/feature-table.metagenome.L3.txt -c KEGG_Pathways -l 3 -f
export PYTHONPATH=
cd closedRef_forPICRUSt
source deactivate
source activate qm2
for n3 in 1 2 3;
do echo $n3;
python ${SCRIPTPATH}/convert_percent.py -i feature-table.metagenome.L${n3}.txt;
#perl ${SCRIPTPATH}/get_table_head2.pl percent.feature-table.metagenome.L${n3}.txt 35 -trantab > percent.feature-table.metagenome.L${n3}.tab
#perl ${SCRIPTPATH}/top10_bar_diagram.pl -right -grid -rotate='-45' -x_title 'Sample Name' -y_title 'Relative Abundance' --y_mun 0.25,4 --height 350 -table percent.feature-table.metagenome.L${n3}.tab > percent.feature-table.metagenome.L${n3}.svg
Rscript ${SCRIPTPATH}/abundance_barplot.R -n 20 -m $mapping_file -c $category_set -i feature-table.metagenome.L${n3}.txt -o function-bar-plots-top20/ -p L${n3}_${category_set}_ -b F -s T;
Rscript ${SCRIPTPATH}/abundance_barplot.R -n 20 -m $mapping_file -c $category_set -i feature-table.metagenome.L${n3}.txt -o function-bar-plots-top20-group-mean/ -p ${category_set}_L${n3}_mean_ -b T -s T;
perl ${SCRIPTPATH}/cluster.pl -BC -Z -x percent.feature-table.metagenome.L${n3}.txt > level1.relative.tree
perl ${SCRIPTPATH}/draw_tree.pl -bun 0.25,4 -bline -type 4 level1.relative.tree percent.feature-table.metagenome.L${n3}.tab --flank_x 100 > tree.feature-table.metagenome.L${n3}.svg
#${SCRIPTPATH}/PCA.R.pl ${PWD}/percent.feature-table.metagenome.L${n3}.txt 0.2 ${PWD}/PCA_L${n3}
cp $mapping_file ./sample-metadata.PCA.txt
perl -p -i.bak -e 's/#//' ./sample-metadata.PCA.txt
tail -n +2 feature-table.metagenome.L${n3}.txt | grep -v "disease"> feature-table.metagenome.L${n3}.PCA.txt
perl -p -i.bak -e 's/#OTU ID/KEGG_function/' feature-table.metagenome.L${n3}.PCA.txt
done;
for svg_file in *svg; do echo $svg_file; base=$(basename $svg_file .svg); rsvg-convert -h 3200 -b white $svg_file > ${base}.png; done
cd ..
for n5 in 1 2 3;
do echo $n5;
for category_1 in $category_set;do echo $category_1;Rscript ${SCRIPTPATH}/Function_PCA.r -i ${PWD}/closedRef_forPICRUSt/feature-table.metagenome.L${n5}.PCA.txt -m ${PWD}/closedRef_forPICRUSt//sample-metadata.PCA.txt -g $category_1;done;
for category_1 in $category_set;do echo $category_1; Rscript ${SCRIPTPATH}/Function_DunnTest.r -i ${PWD}/closedRef_forPICRUSt/feature-table.metagenome.L${n5}.PCA.txt -m ${PWD}/closedRef_forPICRUSt/sample-metadata.PCA.txt -c $category_1 > /dev/null; done;
done;
source deactivate
for category_1 in $category_set;
do echo $category_1;
function_barplot.R -i ./closedRef_forPICRUSt/feature-table.metagenome.L3.txt -m $mapping_file -c $category_1 -j T -a 0.05 -b T -o ./2-ANOVA_And_Duncan
function_barplot.R -i ./closedRef_forPICRUSt/feature-table.metagenome.L3.txt -m $mapping_file -c $category_1 -j T -a 0.05 -b F -o ./2-ANOVA_And_Duncan
done;
fi;
source deactivate
source activate qiime2-2018.11
echo "##############################################################\n#Make phylogenetic trees for ITOL"
<<COMMENT
mkdir phylogeny
qiime feature-table filter-features --i-table table.qza --p-min-frequency $min_freq --o-filtered-table phylogeny/table.${min_freq}.qza
qiime tools export --input-path phylogeny/table.${min_freq}.qza --output-path phylogeny
biom convert -i phylogeny/feature-table.biom -o phylogeny/feature-table.txt --to-tsv
cut -f1 phylogeny/feature-table.txt | tail -n +3 > phylogeny/feature-table.list
seqtk subseq exported/dna-sequences.fasta phylogeny/feature-table.list > phylogeny/dna-sequences.${min_freq}.fasta
qiime tools import --input-path phylogeny/dna-sequences.${min_freq}.fasta --output-path phylogeny/dna-sequences.${min_freq}.qza --type 'FeatureData[Sequence]'
qiime alignment mafft --i-sequences phylogeny/dna-sequences.${min_freq}.qza --o-alignment phylogeny/dna-sequences.${min_freq}.aligned.qza
qiime alignment mask --i-alignment phylogeny/dna-sequences.${min_freq}.aligned.qza --o-masked-alignment phylogeny/dna-sequences.${min_freq}.aligned.masked.qza
qiime phylogeny fasttree --i-alignment phylogeny/dna-sequences.${min_freq}.aligned.masked.qza --o-tree phylogeny/dna-sequences.${min_freq}.unrooted-tree.qza
qiime phylogeny midpoint-root --i-tree phylogeny/dna-sequences.${min_freq}.unrooted-tree.qza --o-rooted-tree phylogeny/dna-sequences.${min_freq}.rooted-tree.qza
qiime feature-classifier classify-sklearn --i-classifier $reference_trained --i-reads phylogeny/dna-sequences.${min_freq}.qza --o-classification phylogeny/taxonomy.${min_freq}.qza
biom add-metadata -i phylogeny/feature-table.biom -o phylogeny/feature-table.taxonomy.biom --observation-metadata-fp exported/taxonomy.tsv --observation-header OTUID,taxonomy,confidence
biom convert -i phylogeny/feature-table.taxonomy.biom -o phylogeny/feature-table.taxonomy.txt --to-tsv --header-key taxonomy
qiime tools export --input-path phylogeny/dna-sequences.${min_freq}.rooted-tree.qza --output-path phylogeny/
mv phylogeny/tree.nwk phylogeny/tree.rooted.nwk
perl ${SCRIPTPATH}/generate_file_Itol.pl phylogeny/feature-table.taxonomy.txt
COMMENT
qiime tools export --input-path masked-aligned-rep-seqs.qza --output-path ./
qiime tools export --input-path rep-seqs.qza --output-path ./
qiime tools export --input-path rooted-tree.qza --output-path ./
echo "##############################################################\n#export all qzv files into clickable folders"
#for f in $(find . -type f -name "*.qzv"); do echo $f; qiime tools export $f --output-dir ${f}.exported; done
for f in $(find . -type f -name "*.qzv"); do echo $f; base=$(basename $f .qzv); dir=$(dirname $f); new=${dir}/${base}; qiime tools export --input-path $f --output-path ${new}.qzv.exported; done
echo "##############################################################\n#Run Qiime1 for differOTU analysis"
source deactivate
source activate qm1
mkdir exported/DiffAbundance
biom convert -i exported/Relative/otu_table.even.txt -o exported/DiffAbundance/otu_table.even.biom --to-hdf5 --table-type="OTU table" --process-obs-metadata taxonomy
summarize_taxa.py -i exported/DiffAbundance/otu_table.even.biom -a -o exported/DiffAbundance/tax
summarize_taxa.py -i exported/DiffAbundance/otu_table.even.biom -a -L 7 -o exported/DiffAbundance/tax
source ~/.bash_profile
min_observation=$(echo \(`wc -l $mapping_file | sed 's/ .*//g'`-1\)/4 | bc)
echo "###############min observation of otu in samples is $min_observation"
mkdir tables_for_deseq_anova_kruskal
for n4 in 2 3 4 5 6 7;
do echo $n4;
#the biom file should include taxonomy information for group_significance.py script
cut -f1 exported/DiffAbundance/tax/otu_table.even_L${n4}.txt > exported/DiffAbundance/tax/otu_table.even_L${n4}.1stColumn.txt
perl -p -i.bak -e 's/#OTU ID/taxonomy/' exported/DiffAbundance/tax/otu_table.even_L${n4}.1stColumn.txt
paste exported/DiffAbundance/tax/otu_table.even_L${n4}.txt exported/DiffAbundance/tax/otu_table.even_L${n4}.1stColumn.txt > exported/DiffAbundance/tax/otu_table.even_${tax_levels[${n4}]}.taxonomy.txt
biom convert -i exported/DiffAbundance/tax/otu_table.even_${tax_levels[${n4}]}.taxonomy.txt -o exported/DiffAbundance/tax/otu_table.even_${tax_levels[${n4}]}.taxonomy.biom --to-hdf5 --table-type="OTU table" --process-obs-metadata taxonomy
cp exported/DiffAbundance/tax/otu_table.even_${tax_levels[${n4}]}.taxonomy.txt tables_for_deseq_anova_kruskal/
filter_otus_from_otu_table.py -i exported/DiffAbundance/tax/otu_table.even_${tax_levels[${n4}]}.taxonomy.biom -s $min_observation -o filtered_otu_table.biom
for category_1 in $category_set;
do echo $category_1;
#Rscript ${SCRIPTPATH}/clean_na_of_inputs.R -m $mapping_file --group $category_1 -o media_files
group_significance.py -i filtered_otu_table.biom -m $mapping_file -c $category_1 -s kruskal_wallis -o exported/DiffAbundance/kruskal_wallis_${category_1}_DiffAbundance_${tax_levels[${n4}]}.txt --biom_samples_are_superset --print_non_overlap;
group_significance.py -i filtered_otu_table.biom -m $mapping_file -c $category_1 -s ANOVA -o exported/DiffAbundance/ANOVA_${category_1}_DiffAbundance_${tax_levels[${n4}]}.txt --biom_samples_are_superset --print_non_overlap;
# python ${SCRIPTPATH}/auto_DESeq.py -m $mapping_file -g $category_1 -l ${tax_levels[${n4}]};
done;
for category_1 in $category_set;
do echo $category_1;
#Rscript ${SCRIPTPATH}/clean_na_of_inputs.R -m $mapping_file --group $category_1 -o media_files
# group_significance.py -i filtered_otu_table.biom -m $mapping_file -c $category_1 -s kruskal_wallis -o exported/DiffAbundance/kruskal_wallis_${category_1}_DiffAbundance_${tax_levels[${n4}]}.txt --biom_samples_are_superset --print_non_overlap;
# group_significance.py -i filtered_otu_table.biom -m $mapping_file -c $category_1 -s ANOVA -o exported/DiffAbundance/ANOVA_${category_1}_DiffAbundance_${tax_levels[${n4}]}.txt --biom_samples_are_superset --print_non_overlap;
python3 ${SCRIPTPATH}/auto_DESeq.py -m $mapping_file -g $category_1 -l ${tax_levels[${n4}]};
done;
done;
echo "##############################################################\n#Run R script for additional R related figure generation"
source deactivate
source activate qm2
mkdir R_output
#Change format of meta-data file for Rscript of PLSDA analysis
#cp $mapping_file ./R_output/sample-metadata.txt
#tail -n +2 exported/feature-table.txt > ./R_output/feature-table.PLSDA.txt
#perl -p -i.bak -e 's/#OTU ID//' ./R_output/feature-table.PLSDA.txt
#sort ./R_output/sample-metadata.txt > ./R_output/sample-metadata.PLSDA.txt
#Change format of meta-data file for Rscript of alpha diversity analysis
#cp $mapping_file ./alpha/sample-metadata_alphadiversity.txt
#perl -p -i.bak -e 's/#SampleID//' ./alpha/sample-metadata_alphadiversity.txt
source deactivate
source activate qm2
for category_1 in $category_set;
do echo $category_1;
Rscript ${SCRIPTPATH}/clean_na_of_inputs.R -m $mapping_file --group $category_1 -o media_files
map=$(readlink -f ./media_files/cleaned_map.txt)
#otu=$(readlink -f ./media_files/cleaned_feature_table.txt)
Rscript ${SCRIPTPATH}/RRelatedOutput.R $map $category_1 T;
Rscript ${SCRIPTPATH}/alphaboxplotwitSig.R -m $map -c $category_1 -i ./alpha/alpha-summary.tsv -o ./alpha/;
done;
source deactivate
source activate qm2
Rscript ${SCRIPTPATH}/beta_heatmap.R -i exported/feature-table.ConsensusLineage.txt -m $mapping_file -t exported/tree.rooted.nwk -r exported/dna-sequences.fasta -o R_output -c $category_set -p 'unclustered_';
Rscript ${SCRIPTPATH}/beta_heatmap.R -i exported/feature-table.ConsensusLineage.txt -t exported/tree.rooted.nwk -r exported/dna-sequences.fasta -o R_output;
perl ${SCRIPTPATH}/table_data_svg.pl --colors cyan-orange R_output/bray_curtis_matrix.xls R_output/weighted_unifrac_matrix.xls R_output/unweighted_unifrac_matrix.xls --symbol 'Beta Diversity' > R_output/BetaDiversity_heatmap.svg
rsvg-convert -h 3200 -b white R_output/BetaDiversity_heatmap.svg > R_output/BetaDiversity_heatmap.png
#python2 ${SCRIPTPATH}/biom_to_stamp.py -m KEGG_Pathways closedRef_forPICRUSt/feature-table.metagenome.biom > closedRef_forPICRUSt/feature-table.metagenome.KEGG_Pathways.STAMP.txt
echo "##############################################################\n#Generate the absolute directory for enviromental factors relational analysis"
# cd exported/
perl ${SCRIPTPATH}/stat_otu_tab.unspecifiedadded.pl -unif min exported/feature-table.taxonomy.txt --prefix exported/Absolute/otu_table -nomat -abs -spestat exported/Absolute/classified_stat.xls
# cd exported/Absolute/
for key in ${!tax_aa[*]};do mv exported/Absolute/otu_table.${key}.absolute.mat exported/Absolute/otu_table.${tax_aa[$key]}.absolute.txt;done;
#mv otu_table.k.absolute.mat otu_table.Kingdom.absolute.txt
#mv otu_table.p.absolute.mat otu_table.Pylumn.absolute.txt
#mv otu_table.c.absolute.mat otu_table.Class.absolute.txt
#mv otu_table.o.absolute.mat otu_table.Order.absolute.txt
#mv otu_table.f.absolute.mat otu_table.Family.absolute.txt
#mv otu_table.g.absolute.mat otu_table.Genus.absolute.txt
#mv otu_table.s.absolute.mat otu_table.Species.absolute.txt
# mkdir RDA
# for n6 in "Phylum" "Class" "Order" "Family" "Genus" "Species";
# do echo $n6;
# mkdir RDA/${n6}
# cp otu_table.${n6}.absolute.txt RDA/${n6}
# cd RDA/${n6}
# for category_1 in $category_set;do echo $category_1;python ${SCRIPTPATH}/RDA.py -i otu_table.${n6}.absolute.txt -m $mapping_file -g $category_1 -o ./ -n 25 -e $not_rda;done;
# cd ../../
# done;
# cd ../../
perl ${SCRIPTPATH}/stat_otu_tab.pl -unif min exported/feature-table.taxonomy.txt -prefix otu_table_forlefse/otu_table
for key in ${!tax_aa[*]};do mv otu_table_forlefse/otu_table.${key}.relative.mat otu_table_forlefse/otu_table.${tax_aa[$key]}.relative.txt;done;
source deactivate
source activate qm2
<<skip
test=${not_rda// */}
if [ ! $test == "all" ];then
echo "##############################################################\nCorrelation heatmap analysis"
for nrda in $not_rda;
do echo $nrda;
prefix=${nrda//,/_}_excluded_;
prefix=${prefix//none_excluded_/};
prefix=${prefix//\//-};
prefix=${prefix//\\/-};
prefix=${prefix//\(/};
prefix=${prefix//\)/};
prefix=${prefix//\%/};
for n7 in "Phylum" "Class" "Order" "Family" "Genus" "Species";
do echo $n7;
Rscript ${SCRIPTPATH}/cor_heatmap.R -i otu_table_forlefse/otu_table.${n7}.relative.txt -o 2-CorrelationHeatmap/${n7}/ -n 25 -m $mapping_file -e $nrda -p "$prefix";
for category_1 in $category_set;do echo $category_1;Rscript ${SCRIPTPATH}/RDA.R -i exported/Relative/otu_table.${n7}.relative.txt -m $mapping_file -c $category_1 -o exported/Absolute/RDA/${n7} -n 25 -e $nrda -p "$prefix";done;
done;
done;
fi;
skip
test=${not_rda// */}
if [ ! $test == "all" ];then
echo "##############################################################\nCorrelation heatmap analysis"
for nrda in $not_rda;
do echo $nrda;
arr=(${nrda//:/ });
nrda=${arr[0]};
prefix=${arr[1]};
for n7 in "Phylum" "Class" "Order" "Family" "Genus" "Species";
do echo $n7;
Rscript ${SCRIPTPATH}/cor_heatmap.R -i otu_table_forlefse/otu_table.${n7}.relative.txt -o 2-CorrelationHeatmap/${n7}/ -n 25 -m $mapping_file -e $nrda -p "$prefix";
for category_1 in $category_set;do echo $category_1;Rscript ${SCRIPTPATH}/RDA.R -i exported/Relative/otu_table.${n7}.relative.txt -m $mapping_file -c $category_1 -o exported/Absolute/RDA/${n7} -n 25 -e $nrda -p "$prefix";done;
done;
done;
fi;
source deactivate
source activate qm2
echo "##############################################################network and abundance heatmap"
for n7 in "Phylum" "Class" "Order" "Family" "Genus" "Species";
do echo $n7;
Rscript ${SCRIPTPATH}/network.R -c 0.5 -i otu_table_forlefse/otu_table.${n7}.relative.txt -o 3-NetworkAnalysis/${n7}/;
#Rscript ${SCRIPTPATH}/abundance_heatmap.R -n 20 -i exported/Relative/otu_table.${n7}.relative.txt -o Heatmap_top20/${n7}/;
Rscript ${SCRIPTPATH}/abundance_heatmap.R -m $mapping_file -c $category_set -n 20 -i exported/Absolute/otu_table.${n7}.absolute.txt -o Heatmap_top20/${n7}/ -l T -t F;
Rscript ${SCRIPTPATH}/abundance_heatmap.R -m $mapping_file -c $category_set -n 20 -i exported/Absolute/otu_table.${n7}.absolute.txt -o Heatmap_top20_clustered/${n7}/ -l T -t F -u T;
Rscript ${SCRIPTPATH}/abundance_heatmap.R -m $mapping_file -c $category_set -n 20 -i exported/Absolute/otu_table.${n7}.absolute.txt -o Heatmap_top20/${n7}/ -b T -l T -p 'group_mean_' -t T;
done;
echo "###############################################################\nAdditional plot"
mkdir 4-VennAndFlower
for category_1 in $category_set;
do echo $category_1;
Rscript ${SCRIPTPATH}/venn_and_flower_plot.R -i ./exported/feature-table.taxonomy.txt -m $mapping_file -c $category_1 -o ./4-VennAndFlower;
Rscript ${SCRIPTPATH}/phylotree_and_heatmap.R -i ./exported/feature-table.ConsensusLineage.txt -t ./exported/tree.rooted.nwk -m $mapping_file -c $category_1 -o AdditionalPhylogeny/ -n 50
done;
source deactivate
source activate qm2
echo "##############################################################\n#Barplot and RDA according to group mean"
for category_1 in $category_set;
do echo $category_1;
for n7 in "Phylum" "Class" "Order" "Family" "Genus" "Species";
do echo $n7;
Rscript ${SCRIPTPATH}/abundance_barplot.R -n 20 -m $mapping_file -c $category_1 -i exported/Relative/otu_table.${n7}.relative.txt -o taxa-bar-plots-top20-group-ordered/ -p ${n7}_${category_1}_ -b F;
Rscript ${SCRIPTPATH}/abundance_barplot.R -n 20 -m $mapping_file -c $category_1 -i exported/Relative/otu_table.${n7}.relative.txt -o Barplot-of-Group-Mean/ -p ${category_1}_${n7}_mean_ -b T;
done;
done;
<<COMMENT
for n6 in "Phylum" "Class" "Order" "Family" "Genus" "Species";
do echo $n6;
Rscript ${SCRIPTPATH}/collapse_table_with_group_mean.R -i exported/Relative/otu_table.${n6}.relative.txt -m $mapping_file -c Group4 -o media_files -s F
for category_1 in Group3;do echo $category_1;python ${SCRIPTPATH}/RDA.py -i media_files/abundance_table_collapsed_with_group_mean.txt -m media_files/map_collapsed_with_group_mean.txt -g $category_1 -o exported/Absolute/RDA/${n6} -n 25 -e $not_rda;done;
done;
COMMENT
##########alpha rarefacation
Rscript ${SCRIPTPATH}/alphararefaction.R -i alpha-rarefaction.qzv.exported -o alpha-rarefaction-ggplot2
Rscript ${SCRIPTPATH}/alphararefaction.R -i alpha-rarefaction.qzv.exported -o alpha-rarefaction-ggplot2 -m $mapping_file -c $category_set -p "group_mean_"
echo "##############################################################\n#Run LEFSE for Group"
#perl ${SCRIPTPATH}/stat_otu_tab.pl -unif min exported/feature-table.taxonomy.txt -prefix otu_table_forlefse/otu_table
#for key in ${!tax_aa[*]};do mv otu_table_forlefse/otu_table.${key}.relative.mat otu_table_forlefse/otu_table.${tax_aa[$key]}.relative.txt;done;
for n7 in "Phylum" "Class" "Order" "Family" "Genus" "Species";
do echo $n7;
for category_1 in $category_set;
do echo $category_1;
Rscript ${SCRIPTPATH}/write_data_for_lefse.R -i otu_table_forlefse/otu_table.${n7}.relative.txt -m $mapping_file -c $category_1 -o exported/Relative/Lefse/${n7}/${category_1}_${n7}_lefse.txt -u l;
done;
done;
source deactivate
source deactivate
source activate lefse
cd exported/Relative
for n7 in "Phylum" "Class" "Order" "Family" "Genus" "Species";
do echo $n7;
cd Lefse/${n7}
for category_1 in $category_set;
do echo $category_1;
base="${category_1}_${n7}_lefse_LDA2"; format_input.py ${category_1}_${n7}_lefse.txt ${base}.lefseinput.txt -c 2 -u 1 -o 1000000; run_lefse.py ${base}.lefseinput.txt ${base}.LDA.txt -l 2;
${SCRIPTPATH}/mod_lefse-plot_res.py --category $category_1 --map $mapping_file --max_feature_len 200 --orientation h --format pdf ${base}.LDA.txt ${base}.pdf; ${SCRIPTPATH}/mod_lefse-plot_cladogram.py ${base}.LDA.txt --map $mapping_file --category $category_1 ${base}.cladogram.pdf --format pdf;
base="${category_1}_${n7}_lefse_LDA4"; format_input.py ${category_1}_${n7}_lefse.txt ${base}.lefseinput.txt -c 2 -u 1 -o 1000000; run_lefse.py ${base}.lefseinput.txt ${base}.LDA.txt -l 4;
${SCRIPTPATH}/mod_lefse-plot_res.py --category $category_1 --map $mapping_file --max_feature_len 200 --orientation h --format pdf ${base}.LDA.txt ${base}.pdf; ${SCRIPTPATH}/mod_lefse-plot_cladogram.py ${base}.LDA.txt --map $mapping_file --category $category_1 ${base}.cladogram.pdf --format pdf;
done;
cd ../../
done;
cd ../../
# source deactivate
# source activate lefse
# mkdir -p LEfSe/Genus/
# for category_1 in $category_set;
# do echo $category_1;
# Rscript ${SCRIPTPATH}/write_data_for_lefse.R exported/Absolute/otu_table.Genus.absolute.txt $mapping_file $category_1 LEfSe/Genus/${category_1}_table_for_lefse.txt F;
# base="${category_1}_Genus_LEfSe_LDA2"; format_input.py LEfSe/Genus/${category_1}_table_for_lefse.txt LEfSe/Genus/${base}.lefseinput.txt -c 2 -u 1 -o 1000000; run_lefse.py LEfSe/Genus/${base}.lefseinput.txt LEfSe/Genus/${base}.LDA.txt -l 2; ${SCRIPTPATH}/mod_lefse-plot_res.py --dpi 300 LEfSe/Genus/${base}.LDA.txt LEfSe/Genus/${base}.png; ${SCRIPTPATH}/mod_lefse-plot_cladogram.py LEfSe/Genus/${base}.LDA.txt --dpi 300 LEfSe/Genus/${base}.cladogram.png --format png --labeled_stop_lev 4;
# ${SCRIPTPATH}/mod_lefse-plot_res.py --max_feature_len 200 --orientation h --format pdf --dpi 300 LEfSe/Genus/${base}.LDA.txt LEfSe/Genus/${base}.pdf; ${SCRIPTPATH}/mod_lefse-plot_cladogram.py LEfSe/Genus/${base}.LDA.txt --dpi 300 LEfSe/Genus/${base}.cladogram.pdf --format pdf --labeled_stop_lev 4;
# done;
# mkdir -p LEfSe/OTU/
# for category_1 in $category_set;
# do echo $category_1;
# Rscript ${SCRIPTPATH}/write_data_for_lefse.R exported/feature-table.taxonomy.txt $mapping_file $category_1 LEfSe/OTU/${category_1}_table_for_lefse.txt T;
#Rscript ${SCRIPTPATH}/write_data_for_lefse.R exported/Absolute/otu_table.Genus.absolute.txt $mapping_file $category_1 LEfSe/OTU/${category_1}_table_for_lefse.txt F;
# base="${category_1}_OTU_LEfSe_LDA4"; format_input.py LEfSe/OTU/${category_1}_table_for_lefse.txt LEfSe/OTU/${base}.lefseinput.txt -c 2 -u 1 -o 1000000; run_lefse.py LEfSe/OTU/${base}.lefseinput.txt LEfSe/OTU/${base}.LDA.txt -l 4; ${SCRIPTPATH}/mod_lefse-plot_res.py --dpi 300 LEfSe/OTU/${base}.LDA.txt LEfSe/OTU/${base}.png; ${SCRIPTPATH}/mod_lefse-plot_cladogram.py LEfSe/OTU/${base}.LDA.txt --dpi 300 LEfSe/OTU/${base}.cladogram.png --format png ;
# ${SCRIPTPATH}/mod_lefse-plot_res.py --max_feature_len 200 --orientation h --format pdf --dpi 300 LEfSe/OTU/${base}.LDA.txt LEfSe/OTU/${base}.pdf; ${SCRIPTPATH}/mod_lefse-plot_cladogram.py LEfSe/OTU/${base}.LDA.txt --dpi 300 LEfSe/OTU/${base}.cladogram.pdf --format pdf ;
# done;
source deactivate
source activate qm2
category_report=($category_set)
echo "##############################################################\n#Organize the result files";
#cp -r ${SCRIPTPATH}/Result ./
bash ${SCRIPTPATH}/organize_dir_structure_V2.sh $mapping_file $category_report ${SCRIPTPATH} wu $if_picrust $prefix;
if [ -d "../Result/${category_report}" ];then
rm -r ../Result/${category_report};
fi;
mv Result ../Result/${category_report}
cd ../;
done;