Merge branch 'develop' into 'master'

Develop

See merge request !9

Snakefile

@@ -301,15 +301,20 @@ def set_default_values():
     # By default, the importing, filtering and denoising steps will be done one the whole gathered fastq
     set_default_value("global", "parallel-samples", False)
 
-    if "denoiser" in config["global"]:
-        # FASTQ type and format
-        if config["global"]["library-type"] == "single-end":
-            set_default_value("import", "type", "\"SampleData[SequencesWithQuality]\"")
-            set_default_value("import", "input-format", "SingleEndFastqManifestPhred33")
+    # Fill denoiser type
+    if "deblur" in config.keys():
+        config["global"]["denoiser"] = "deblur"
+    elif "dada2" in config.keys():
+        config["global"]["denoiser"] = "dada2"
 
-        else:
-            set_default_value("import", "type", "\"SampleData[PairedEndSequencesWithQuality]\"")
-            set_default_value("import", "input-format", "PairedEndFastqManifestPhred33")
+    # FASTQ type and format
+    if config["global"]["library-type"] == "single-end":
+        set_default_value("import", "type", "\"SampleData[SequencesWithQuality]\"")
+        set_default_value("import", "input-format", "SingleEndFastqManifestPhred33")
+
+    else:
+        set_default_value("import", "type", "\"SampleData[PairedEndSequencesWithQuality]\"")
+        set_default_value("import", "input-format", "PairedEndFastqManifestPhred33")
 
     # Set global multithreading parameter
     set_default_value("global", "nbthreads", 1)
@@ -354,6 +359,7 @@ def set_multithreading():
 ##    WORKFLOW FUNCTIONS    ##
 ##############################
 
+
 def parallel_process():
     """
     Qiime2 is normally a sequential process. Unfortunately, when dealing with a lot of samples, it can
@@ -481,6 +487,8 @@ def getInput(tool, given_file=""):
     if tool == "alpha_rarefaction":
         if given_file == "table.qza":
             return getOutput("merge_denoiser_results", "table.qza") if config["global"]["parallel-samples"] else getOutput("denoiser", "table.qza")
+        elif given_file == "abundance_table.tsv":
+            return getOutput("export_table_tsv", "abundance_table.tsv")
         else:
             return getOutput("phylogenetic_tree", "rooted-tree.qza")
 
@@ -593,6 +601,8 @@ def format_all_rule():
         all_input.append(getOutput("summarize_table", "table.qzv"))
         all_input.append(getOutput("export_table_tsv", "abundance_table.tsv"))
 
+        all_input.append(getOutput("alpha_rarefaction", "results/index.html"))
+
         if config["global"]["parallel-samples"]:
             all_input.append(getOutput("merge_denoiser_stats", "html"))
 
@@ -602,9 +612,7 @@ def format_all_rule():
 
     if "taxonomy" in config.keys():
         all_input.append(getOutput("taxonomy", "barplot/index.html"))
-
-    if "alpha-rarefaction" in config.keys():
-        all_input.append(getOutput("alpha_rarefaction", "results/index.html"))
+        all_input.append(getOutput("summarize_table", "plots"))
 
     if "ancom" in config.keys():
         all_input.append(getOutput("ancom", "volcano/index.html"))
@@ -666,83 +674,83 @@ rule multiqc:
     echo "\nMultiQc.....OK" >> {params.logfile}
     """
 
-if "denoiser" in config["global"]:
-    ########################
-    ##    IMPORT FASTQ    ##
-    ########################
-
-    # Split the main manifest file into several ones (one per sample) to parallellize the tasks
-    rule split_manifest:
-        input: getInput("split_manifest")
-        output: getOutput("split_manifest", "manifest.csv")
-        run:
-            import os
-            import pandas
+########################
+##    IMPORT FASTQ    ##
+########################
 
-            df = pd.read_csv(config["global"]["manifest"], comment="#")
-            if wildcards.sample_id == 'All':
-                df.to_csv(output[0], index=False)
-            else:
-                minDf = df[df["sample-id"].astype(str) == wildcards.sample_id]
-                minDf.to_csv(output[0], index=False)
+# Split the main manifest file into several ones (one per sample) to parallellize the tasks
+rule split_manifest:
+    input: getInput("split_manifest")
+    output: getOutput("split_manifest", "manifest.csv")
+    run:
+        import os
+        import pandas
 
-    # Import Fastq files into a QIIME2 artifact
-    rule import:
-        input: getInput("import")
-        output: getOutput("import", "import.qza")
-        conda: qiime2_yml
-        params: options = getOptions("import")
-        shell: """
-        qiime tools import --input-path {input} --output-path {output} {params.options}
-        """
+        df = pd.read_csv(config["global"]["manifest"], comment="#")
+        if wildcards.sample_id == 'All':
+            df.to_csv(output[0], index=False)
+        else:
+            minDf = df[df["sample-id"].astype(str) == wildcards.sample_id]
+            minDf.to_csv(output[0], index=False)
+
+# Import Fastq files into a QIIME2 artifact
+rule import:
+    input: getInput("import")
+    output: getOutput("import", "import.qza")
+    conda: qiime2_yml
+    params: options = getOptions("import")
+    shell: """
+    qiime tools import --input-path {input} --output-path {output} {params.options}
+    """
 
-    #####################
-    ##    FILTERING    ##
-    #####################
+#####################
+##    FILTERING    ##
+#####################
 
-    rule cutadapt:
-        input: getInput("cutadapt")
-        output: getOutput("cutadapt", "cutadapt.qza")
-        conda: qiime2_yml
-        params: options = getOptions("cutadapt"),
-            lib_type = pairedOrSingle("cutadapt")
-        shell: """
-        qiime cutadapt {params.lib_type} --i-demultiplexed-sequences {input} --o-trimmed-sequences {output} {params.options}
-        """
+rule cutadapt:
+    input: getInput("cutadapt")
+    output: getOutput("cutadapt", "cutadapt.qza")
+    conda: qiime2_yml
+    params: options = getOptions("cutadapt"),
+        lib_type = pairedOrSingle("cutadapt")
+    shell: """
+    qiime cutadapt {params.lib_type} --i-demultiplexed-sequences {input} --o-trimmed-sequences {output} --p-discard-untrimmed {params.options}
+    """
 
-    # If the library is paired-end, reads need to be joined together for further analysis
-    # ONLY WHEN DEBLUR IS USED AS DENOISER
-    rule join_pairs:
-        input: getInput("join_pairs")
-        output: getOutput("join_pairs", "joined_sequences.qza")
-        conda: qiime2_yml
-        shell: """
-        qiime vsearch join-pairs --i-demultiplexed-seqs {input} --o-joined-sequences {output}
-        """
+# If the library is paired-end, reads need to be joined together for further analysis
+# ONLY WHEN DEBLUR IS USED AS DENOISER
+rule join_pairs:
+    input: getInput("join_pairs")
+    output: getOutput("join_pairs", "joined_sequences.qza")
+    conda: qiime2_yml
+    shell: """
+    qiime vsearch join-pairs --i-demultiplexed-seqs {input} --o-joined-sequences {output}
+    """
 
-    # Filter reads on quality
-    # ONLY WHEN DEBLUR IS USED AS DENOISER
-    rule quality_filter:
-        input: getInput("quality_filter")
-        output: getOutput("quality_filter", "filtered_sequences.qza"),
-            getOutput("quality_filter", "filter_stats.qza"),
-            getOutput("quality_filter", "filter_stats.qzv"),
-            directory(getOutput("quality_filter", "html")),
-            getOutput("quality_filter", "stats/stats.csv")
-
-        params: options = getOptions("quality-filter"),
-            lib_type = pairedOrSingle("quality_filter")
-        conda: qiime2_yml
-        shell: """
-        qiime quality-filter {params.lib_type} --i-demux {input} --o-filtered-sequences {output[0]}  --o-filter-stats {output[1]} {params.options}
-        qiime metadata tabulate --m-input-file {output[1]} --o-visualization {output[2]}
-        qiime tools export --input-path {output[2]} --output-path {output[3]}
-        qiime tools export --input-path {output[1]} --output-path `dirname {output[4]}`
-        """
+# Filter reads on quality
+# ONLY WHEN DEBLUR IS USED AS DENOISER
+rule quality_filter:
+    input: getInput("quality_filter")
+    output: getOutput("quality_filter", "filtered_sequences.qza"),
+        getOutput("quality_filter", "filter_stats.qza"),
+        getOutput("quality_filter", "filter_stats.qzv"),
+        directory(getOutput("quality_filter", "html")),
+        getOutput("quality_filter", "stats/stats.csv")
+
+    params: options = getOptions("quality-filter"),
+        lib_type = pairedOrSingle("quality_filter")
+    conda: qiime2_yml
+    shell: """
+    qiime quality-filter {params.lib_type} --i-demux {input} --o-filtered-sequences {output[0]}  --o-filter-stats {output[1]} {params.options}
+    qiime metadata tabulate --m-input-file {output[1]} --o-visualization {output[2]}
+    qiime tools export --input-path {output[2]} --output-path {output[3]}
+    qiime tools export --input-path {output[1]} --output-path `dirname {output[4]}`
+    """
 
     #####################
     ##    DENOISING    ##
     #####################
+if "denoiser" in config["global"]:
 
     # Deblur denoiser : produces an OTU table
     rule deblur:
@@ -942,59 +950,90 @@ if "denoiser" in config["global"]:
                 getOutput("diversity", "unweighted_unifrac_pcoa_results.qza"),
                 getOutput("diversity", "weighted_unifrac_pcoa_results.qza"),
                 getOutput("diversity", "jaccard_pcoa_results.qza"),
-                getOutput("diversity", "bray_curits_pcoa_results.qza"),
+                getOutput("diversity", "bray_curtis_pcoa_results.qza"),
                 getOutput("diversity", "unweighted_unifrac_emperor.qzv"),
                 getOutput("diversity", "weighted_unifrac_emperor.qzv"),
                 getOutput("diversity", "jaccard_emperor.qzv"),
                 getOutput("diversity", "bray_curtis_emperor.qzv"),
-                braycurtis = directory(getOutput("diversity", "pcoa/bray_curtis")),
-                jaccard = directory(getOutput("diversity", "pcoa/jaccard")),
-                unweighted_unifrac = directory(getOutput("diversity", "pcoa/unweighted_unifrac")),
-                html = getOutput("diversity", "pcoa/weighted_unifrac/emperor.html")
+                braycurtis_pcoa = directory(getOutput("diversity", "pcoa/bray_curtis")),
+                jaccard_pcoa = directory(getOutput("diversity", "pcoa/jaccard")),
+                unweighted_unifrac_pcoa = directory(getOutput("diversity", "pcoa/unweighted_unifrac")),
+                weighted_unifrac_pcoa = getOutput("diversity", "pcoa/weighted_unifrac/emperor.html")
             params: options = getOptions("diversity"),
                 logfile = config["global"]["outdir"] + "/" + LOGFILE
             conda: qiime2_yml
             shell: """
             qiime diversity core-metrics-phylogenetic --i-phylogeny {input[0]} --i-table  {input[1]}  --m-metadata-file {input[2]} --o-rarefied-table {output[0]} --o-faith-pd-vector {output[1]} --o-observed-otus-vector {output[2]} --o-shannon-vector {output[3]} --o-evenness-vector {output[4]} --o-unweighted-unifrac-distance-matrix {output[5]} --o-weighted-unifrac-distance-matrix {output[6]} --o-jaccard-distance-matrix {output[7]} --o-bray-curtis-distance-matrix {output[8]} --o-unweighted-unifrac-pcoa-results {output[9]} --o-weighted-unifrac-pcoa-results {output[10]} --o-jaccard-pcoa-results {output[11]} --o-bray-curtis-pcoa-results {output[12]} --o-unweighted-unifrac-emperor {output[13]} --o-weighted-unifrac-emperor {output[14]} --o-jaccard-emperor {output[15]} --o-bray-curtis-emperor {output[16]} {params.options}
-            qiime tools export --input-path {output[16]} --output-path {output.braycurtis}
-            qiime tools export --input-path {output[15]} --output-path {output.jaccard}
-            qiime tools export --input-path {output[13]} --output-path {output.unweighted_unifrac}
-            qiime tools export --input-path {output[14]} --output-path `dirname {output.html}`
+            qiime tools export --input-path {output[16]} --output-path {output.braycurtis_pcoa}
+            qiime tools export --input-path {output[15]} --output-path {output.jaccard_pcoa}
+            qiime tools export --input-path {output[13]} --output-path {output.unweighted_unifrac_pcoa}
+            qiime tools export --input-path {output[14]} --output-path `dirname {output.weighted_unifrac_pcoa}`
+            python scripts/export_diversity.py {outdir}/diversity
             echo "\nDiversity.....OK" >> {params.logfile}
             """
 
         rule alpha_group_significance:
             input: getInput("alpha_group_significance", "shannon_vector.qza"),
                 getInput("alpha_group_significance", "evenness_vector.qza"),
+                getInput("alpha_group_significance", "faith_pd_vector.qza"),
+                getInput("alpha_group_significance", "observed_otus_vector.qza"),
                 config["global"]["context"]
-            output: getOutput("alpha_group_significance", "shannon-group-significance/index.html"),
+            output: getOutput("alpha_group_significance", "shannon-group-significance.qzv"),
+                getOutput("alpha_group_significance", "evenness-group-significance.qzv"),
+                getOutput("alpha_group_significance", "faith_pd_vector.qzv"),
+                getOutput("alpha_group_significance", "observed_otus_vector.qzv"),
+                getOutput("alpha_group_significance", "shannon-group-significance/index.html"),
                 getOutput("alpha_group_significance", "evenness-group-significance/index.html"),
-                getOutput("alpha_group_significance", "shannon-group-significance.qzv"),
-                getOutput("alpha_group_significance", "evenness-group-significance.qzv")
+                getOutput("alpha_group_significance", "faith_pd-group-significance/index.html"),
+                getOutput("alpha_group_significance", "observed_otus-group-significance/index.html")
             conda: qiime2_yml
             shell: """
-            qiime diversity alpha-group-significance   --i-alpha-diversity {input[0]}  --m-metadata-file {input[2]}  --o-visualization {output[2]}
-            qiime diversity alpha-group-significance   --i-alpha-diversity {input[1]}  --m-metadata-file {input[2]}  --o-visualization {output[3]}
-            qiime tools export --input-path {output[2]} --output-path `dirname {output[0]}`
-            qiime tools export --input-path {output[3]} --output-path `dirname {output[1]}`
-
+            qiime diversity alpha-group-significance   --i-alpha-diversity {input[0]}  --m-metadata-file {input[4]}  --o-visualization {output[0]}
+            qiime diversity alpha-group-significance   --i-alpha-diversity {input[1]}  --m-metadata-file {input[4]}  --o-visualization {output[1]}
+            qiime diversity alpha-group-significance   --i-alpha-diversity {input[2]}  --m-metadata-file {input[4]}  --o-visualization {output[2]}
+            qiime diversity alpha-group-significance   --i-alpha-diversity {input[3]}  --m-metadata-file {input[4]}  --o-visualization {output[3]}
+            qiime tools export --input-path {output[0]} --output-path `dirname {output[4]}`
+            qiime tools export --input-path {output[1]} --output-path `dirname {output[5]}`
+            qiime tools export --input-path {output[2]} --output-path `dirname {output[6]}`
+            qiime tools export --input-path {output[3]} --output-path `dirname {output[7]}`
             """
 
-    # Alpha rarefaction
-    if "alpha-rarefaction" in config.keys():
+    # Write the alpha rarefaction max depth parameter into a file
+    rule prepare_alpha_rarefaction:
+        input: getInput("alpha_rarefaction", "abundance_table.tsv")
+        output: getOutput("export_table_tsv", "alpha-rarefaction_maxdepth.txt")
+        run:
 
-        rule alpha_rarefaction:
-            input: getInput("alpha_rarefaction", "table.qza"),
-                getInput("alpha_rarefaction", "rooted-tree.qza"),
-                config["global"]["context"]
-            output: getOutput("alpha_rarefaction", "alpha_rarefaction.qzv"),
-                getOutput("alpha_rarefaction", "results/index.html")
-            params: options = getOptions("alpha-rarefaction")
-            conda: qiime2_yml
-            shell: """
-            qiime diversity alpha-rarefaction --i-table {input[0]} --i-phylogeny  {input[1]} --m-metadata-file  {input[2]} --o-visualization {output[0]} {params.options}
-            qiime tools export --input-path {output[0]} --output-path `dirname {output[1]}`
-            """
+            # If an alpha rarefaction is already given by the user, we get it
+            if "alpha-rarefaction" in config.keys() and "p-max-depth" in config["alpha-rarefaction"].keys():
+                max_depth = config["alpha-rarefaction"]["p-max-depth"]
+            # Otherwise we take the median value across sample depth
+            else:
+                df = pd.read_csv(input[0], sep="\t", index_col=0)
+                max_depth = int(df.sum().median())
+                if "alpha-rarefaction" not in config.keys():
+                    config["alpha-rarefaction"] = dict()
+                config["alpha-rarefaction"]["p-max-depth"] = max_depth
+
+            # Write max rarefaction parameter into a file
+            f = open(output[0], 'w')
+            f.write(str(max_depth))
+            f.close()
+
+    # Alpha rarefaction
+    rule alpha_rarefaction:
+        input: getInput("alpha_rarefaction", "table.qza"),
+            getInput("alpha_rarefaction", "rooted-tree.qza"),
+            config["global"]["context"],
+            getOutput("export_table_tsv", "alpha-rarefaction_maxdepth.txt")
+        output: getOutput("alpha_rarefaction", "alpha_rarefaction.qzv"),
+            getOutput("alpha_rarefaction", "results/index.html")
+        conda: qiime2_yml
+        shell: """
+        RAREFACTION_MAX_DEPTH=$(cat {input[3]})
+        qiime diversity alpha-rarefaction --i-table {input[0]} --i-phylogeny  {input[1]} --m-metadata-file  {input[2]} --o-visualization {output[0]} --p-max-depth $RAREFACTION_MAX_DEPTH
+        qiime tools export --input-path {output[0]} --output-path `dirname {output[1]}`
+        """
 
     # Taxonomy
     if 'taxonomy' in config.keys():
@@ -1008,6 +1047,7 @@ if "denoiser" in config["global"]:
                 getOutput("taxonomy", "taxa-bar-plots.qzv"),
                 getOutput("taxonomy", "taxons/index.html"),
                 getOutput("taxonomy", "barplot/index.html"),
+                getOutput("taxonomy", "taxons/metadata.tsv")
             conda: qiime2_yml
             params: options = getOptions("taxonomy", ["classifier"]),
                 logfile = config["global"]["outdir"] + "/" + LOGFILE
@@ -1020,6 +1060,14 @@ if "denoiser" in config["global"]:
             echo "\nTaxonomy.....OK" >> {params.logfile}
           """
 
+    rule prevalence_abundance:
+        input: getOutput("export_table_tsv", "abundance_table.tsv"),
+            getOutput("taxonomy", "taxons/metadata.tsv")
+        output: directory(getOutput("summarize_table", "plots"))
+        shell: """
+        python scripts/plot_prevalence_abundance.py {input[0]} {input[1]} {output}
+        """
+
     # ANCOM (differential expression)
     if 'ancom' in config.keys():
 
@@ -1040,6 +1088,20 @@ if "denoiser" in config["global"]:
                 """
 
 
+############################
+##      BUILD REPORT       #
+############################
+
+rule build_report:
+    output:
+        outdir + "/report.tar.gz"
+    shell: """
+    python scripts/build_report/build_report.py {outdir}
+    tar czvf {output} -C {outdir} report
+    rm -r {outdir}/report
+    """
+
+
 ###########################
 ##      CLEAN RULES      ##
 ###########################

conda/microSysMics.yml

@@ -3,5 +3,8 @@ dependencies :
 - bioconda::snakemake
 - pandas
 - python-dateutil
+- git
 - conda-forge::gitpython
 - jsonschema
+- jinja2
+- plotly

config.json

@@ -2,8 +2,7 @@
 	"global" : {
 		"manifest" : "test/manifest.csv",
 		"context" : "test/context.tsv",
-		"denoiser" : "dada2",
-		"outdir" : "out",
+		"outdir" : "out_dada2",
 		"parallel-samples" : false,
 		"nbthreads" : 2
 	},
@@ -14,9 +13,6 @@
     "diversity" : {
         "p-sampling-depth" : 2338
 	},
-	"alpha-rarefaction" : {
-		"p-max-depth" : 5000
-	},
 	"ancom" : {
 		"m-metadata-column" : "time"
 	}

scripts/build_report/build_report.py

+"""
+This script gathers all outputs from the pipeline in an archive
+with an html report.
+"""
+
+from jinja2 import Environment, PackageLoader
+import os.path
+import sys
+import shutil
+
+
+def gather_outputs():
+    """
+    Gather all interesting pipeline outputs (HTML viz, data tables...) in a single directory and feed
+    the template dictionary that will be used to generate the html report.
+    """
+
+    # Create report directory
+    global REPORT_DIR
+    REPORT_DIR = INDIR + "/report"
+    try:
+        shutil.rmtree(REPORT_DIR)
+        print("Removing previous report.")
+    except FileNotFoundError:
+        pass
+    os.mkdir(REPORT_DIR)
+
+    # Get multiqc report
+    if os.path.isfile(INDIR + "/multiqc/multiqc_report.html"):
+        os.mkdir(REPORT_DIR + "/multiqc")
+        shutil.copyfile(INDIR + "/multiqc/multiqc_report.html", REPORT_DIR + "/multiqc/multiqc_report.html")
+        template_data["multiqc_report"] = "multiqc/multiqc_report.html"
+
+    # Get dada2 stats
+    if os.path.isfile(INDIR + "/dada2/html/index.html"):
+        shutil.copytree(INDIR + "/dada2/html", REPORT_DIR + "/dada2/html")
+        template_data["dada2_report"] = "dada2/html/index.html"
+
+    # Get ASV table infos
+    if os.path.isfile(INDIR + "/export_table_tsv/abundance_table.tsv"):
+        shutil.copytree(INDIR + "/export_table_tsv", REPORT_DIR + "/asv_table")
+        shutil.copytree(INDIR + "/summarize_table/seqs_html", REPORT_DIR + "/asv_sequences/seqs_html")
+        shutil.copytree(INDIR + "/summarize_table/table_html", REPORT_DIR + "/asv_table/table_html")
+        template_data["sequences_html"] = "asv_sequences/seqs_html/index.html"
+        template_data["summarize_html"] = "asv_table/table_html/index.html"
+
+    # Get alpha rarefaction data
+    if os.path.isfile(INDIR + "/alpha_rarefaction/results/index.html"):
+        shutil.copytree(INDIR + "/alpha_rarefaction/results", REPORT_DIR + "/alpha_rarefaction")
+        template_data["alpha_rarefaction"] = "alpha_rarefaction/index.html"
+
+    # Get diversity data
+    if os.path.isfile(INDIR + "/diversity/pcoa/bray_curtis/index.html"):
+        shutil.copytree(INDIR + "/diversity/pcoa", REPORT_DIR + "/diversity/pcoa")
+        shutil.copytree(INDIR + "/diversity/tables", REPORT_DIR + "/diversity/tables")
+        template_data["alpha_rarefaction"] = "alpha_rarefaction/index.html"
+
+    # Get alpha group significance data
+    if os.path.isfile(INDIR + "/alpha_group_significance/shannon-group-significance/index.html"):
+        shutil.copytree(INDIR + "/alpha_group_significance/shannon-group-significance", REPORT_DIR + "/diversity/alpha_group_significance/shannon-group-significance")
+        shutil.copytree(INDIR + "/alpha_group_significance/evenness-group-significance", REPORT_DIR + "/diversity/alpha_group_significance/evenness-group-significance")
+        shutil.copytree(INDIR + "/alpha_group_significance/faith_pd-group-significance", REPORT_DIR + "/diversity/alpha_group_significance/faith_pd-group-significance")
+        shutil.copytree(INDIR + "/alpha_group_significance/observed_otus-group-significance", REPORT_DIR + "/diversity/alpha_group_significance/observed_otus-group-significance")
+        template_data["alpha_shannon"] = "diversity/alpha_group_significance/shannon-group-significance/index.html"
+        template_data["alpha_eveness"] = "diversity/alpha_group_significance/evenness-group-significance/index.html"
+        template_data["alpha_faith"] = "diversity/alpha_group_significance/faith_pd-group-significance/index.html"
+        template_data["alpha_observedotus"] = "diversity/alpha_group_significance/observed_otus-group-significance/index.html"
+
+    # Get taxonomic composition
+    if os.path.isfile(INDIR + "/taxonomy/barplot/index.html"):
+        shutil.copytree(INDIR + "/taxonomy/barplot", REPORT_DIR + "/taxonomy/barplot")
+        shutil.copytree(INDIR + "/taxonomy/taxons", REPORT_DIR + "/taxonomy/taxons")
+        template_data["taxo_barplot"] = "taxonomy/barplot/index.html"
+        template_data["taxo_taxons"] = "taxonomy/taxons/index.html"
+
+    # Get Differential abundance
+    if os.path.isfile(INDIR + "/ancom/volcano/index.html"):
+        shutil.copytree(INDIR + "/ancom/volcano", REPORT_DIR + "/ancom/volcano")
+        template_data["ancom_volcano"] = "ancom/volcano/index.html"
+
+    # Get Phylogenetic tree
+    if os.path.isfile(INDIR + "/phylogenetic_tree/tree.nwk"):
+        os.mkdir(REPORT_DIR + "/phylogenetic_tree")
+        shutil.copyfile(INDIR + "/phylogenetic_tree/tree.nwk", REPORT_DIR + "/phylogenetic_tree/tree.nwk")
+        template_data["phylogenetic_tree"] = "phylogenetic_tree/tree.nwk"
+
+
+def build_html_report():
+
+    # Feed HTML template
+    env = Environment(loader=PackageLoader('build_report', '../'))
+    htmlTemplate = env.get_template('build_report/templates/build_report.html')
+    htmlContent = htmlTemplate.render(template_data).encode("utf-8")
+
+    # Export HTML file
+    with open(REPORT_DIR + "/microSysMics.html", 'wb') as f:
+        f.write(htmlContent)
+
+    # Copy bootstrap files
+    shutil.copytree(os.path.dirname(os.path.abspath(__file__)) + "/static", REPORT_DIR + "/.static")
+
+
+if __name__ == "__main__":
+
+    # Get input analysis directory
+    global INDIR
+    INDIR = sys.argv[1]
+
+    # Initialize an empty dictionnary that will feed the template
+    global template_data
+    template_data = dict()
+
+    # Gather all interesting output (HTML viz, data tables...) in a single directory
+    gather_outputs()
+
+    # Build the html report
+    build_html_report()

scripts/build_report/static/bootstrap-3.3.4-dist/css/bootstrap-theme.min.css

+/*!
+ * Bootstrap v3.3.4 (http://getbootstrap.com)
+ * Copyright 2011-2015 Twitter, Inc.
+ * Licensed under MIT (https://github.com/twbs/bootstrap/blob/master/LICENSE)
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\ No newline at end of file

scripts/build_report/static/bootstrap-3.3.4-dist/css/gentelella.min.css

+.row {
+  margin-right: -10px;
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+}
+
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+  margin-top: 20px;
+}
+.tile_count .tile_stats_count {
+  border-bottom: 1px solid #D9DEE4;
+  padding: 0 10px 0 20px;
+  text-overflow: ellipsis;
+  overflow: hidden;
+  white-space: nowrap;
+  position: relative;
+}
+
+@media (min-width: 992px) {
+  footer {
+    margin-left: 230px;
+  }
+}
+
+@media (min-width: 992px) {
+  .tile_count .tile_stats_count {
+    margin-bottom: 10px;
+    border-bottom: 0;
+    padding-bottom: 10px;
+  }
+}
+.tile_count .tile_stats_count:before {
+  content:"";
+  position: absolute;
+  left: 0;
+  height: 65px;
+  border-left: 2px solid #ADB2B5;
+  margin-top: 10px;
+}
+@media (min-width:992px) {
+  .tile_count .tile_stats_count:first-child:before {
+    border-left: 0;
+  }
+}
+.tile_count .tile_stats_count .count {
+  font-size: 30px;
+  line-height: 47px;
+  font-weight: 600;
+}
+@media (min-width:768px) {
+  .tile_count .tile_stats_count .count {
+    font-size: 40px;
+  }
+}
+@media (min-width: 992px) and (max-width: 1100px) {
+  .tile_count .tile_stats_count .count {
+    font-size: 30px;
+  }
+}
+.tile_count .tile_stats_count span {
+  font-size: 12px;
+}
+@media (min-width:768px) {
+  .tile_count .tile_stats_count span {
+    font-size: 13px;
+  }
+}
+.tile_count .tile_stats_count .count_bottom i {
+  width: 12px;
+}
+
+
+/** tile stats **/
+.tile-stats {
+  position: relative;
+  display: block;
+  margin-bottom: 12px;
+  border: 1px solid #E4E4E4;
+  -webkit-border-radius: 5px;
+  overflow: hidden;
+  padding-bottom: 5px;
+  -webkit-background-clip: padding-box;
+  -moz-border-radius: 5px;
+  -moz-background-clip: padding;
+  border-radius: 5px;
+  background-clip: padding-box;
+  background: #FFF;
+  -moz-transition: all 300ms ease-in-out;
+  -o-transition: all 300ms ease-in-out;
+  -webkit-transition: all 300ms ease-in-out;
+  transition: all 300ms ease-in-out;
+}
+
+.tile-stats:hover .icon i {
+  animation-name: tansformAnimation;
+  animation-duration: .5s;
+  animation-iteration-count: 1;
+  color: rgba(58, 58, 58, 0.41);
+  animation-timing-function: ease;
+  animation-fill-mode: forwards;
+  -webkit-animation-name: tansformAnimation;
+  -webkit-animation-duration: .5s;
+  -webkit-animation-iteration-count: 1;
+  -webkit-animation-timing-function: ease;
+  -webkit-animation-fill-mode: forwards;
+  -moz-animation-name: tansformAnimation;
+  -moz-animation-duration: .5s;
+  -moz-animation-iteration-count: 1;
+  -moz-animation-timing-function: ease;
+  -moz-animation-fill-mode: forwards;
+}
+
+.tile-stats .icon {
+  width: 20px;
+  height: 20px;
+  color: #BAB8B8;
+  position: absolute;
+  right: 53px;
+  top: 22px;
+  z-index: 1;
+}
+
+.tile-stats .icon i {
+  margin: 0;
+  font-size: 60px;
+  line-height: 0;
+  vertical-align: bottom;
+  padding: 0;
+}
+
+.tile-stats .count {
+  font-size: 38px;
+  font-weight: bold;
+  line-height: 1.65857143
+}
+
+.tile-stats .count, .tile-stats h3, .tile-stats p {
+  position: relative;
+  margin: 0;
+  margin-left: 10px;
+  z-index: 5;
+  padding: 0;
+}
+
+.tile-stats h3 {
+  color: #BAB8B8;
+}
+
+.tile-stats p {
+  margin-top: 5px;
+  font-size: 12px;
+}
+
+.tile-stats > .dash-box-footer {
+  position: relative;
+  text-align: center;
+  margin-top: 5px;
+  padding: 3px 0;
+  color: #fff;
+  color: rgba(255, 255, 255, 0.8);
+  display: block;
+  z-index: 10;
+  background: rgba(0, 0, 0, 0.1);
+  text-decoration: none;
+}
+
+.tile-stats > .dash-box-footer:hover {
+  color: #fff;
+  background: rgba(0, 0, 0, 0.15);
+}
+
+.tile-stats > .dash-box-footer:hover {
+  color: #fff;
+  background: rgba(0, 0, 0, 0.15);
+}
+
+table.tile_info {
+  padding: 10px 15px;
+}
+
+table.tile_info span.right {
+  margin-right: 0;
+  float: right;
+  position: absolute;
+  right: 4%;
+}
+
+.tile:hover {
+  text-decoration: none;
+}
+
+.tile_header {
+  border-bottom: transparent;
+  padding: 7px 15px;
+  margin-bottom: 15px;
+  background: #E7E7E7;
+}
+
+.tile_head h4 {
+  margin-top: 0;
+  margin-bottom: 5px;
+}
+
+.tiles-bottom {
+  padding: 5px 10px;
+  margin-top: 10px;
+  background: rgba(194, 194, 194, 0.3);
+  text-align: left;
+}
+
+
+
+.blue {
+  color: #3498DB;
+}
+.purple {
+  color: #9B59B6;
+}
+.green {
+  color: #1ABB9C;
+}
+.aero {
+  color: #9CC2CB;
+}
+.red {
+  color: #E74C3C;
+}
+.dark {
+  color: #34495E;
+}
+.grey {
+  color :#7B8483;
+}