Snakemake workflow: 16S rRNA-seq for gastric microbiota

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16s_rrnaseq_gastric
16s_rrnaseq_gastric
16s_rrnaseq_gastric
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Snakemake workflow: 16S rRNA-seq for gastric microbiota

This is a Snakemake workflow encapusulating Qiime2 modules. The codes are distributed in the respective folders under workflow/ , i.e. scripts , rules , and envs . Define the entry point of the workflow in the Snakefile and the main configuration in the ./config/16S-rRNA-seq.yaml file. The .rmd script is used to analyze and visulize Qiime2 outputs.

Project

rRNA gene sequencing of the gastric microbiota of mice

The goal of the rRNA gene sequencing was two-fold: 1) to assess potential effects of the gastrin transgene on the gastric microbiota in INS-GAS mice and 2) to address the potential effects of iron deficiency on the gastric microbiota in INS-GAS mice. Collectively, the rationale of this work was to assess the contribution of the gastric microbiota in the development of precancerous lesions that occur in INS-GAS mice due to the presence of the gastrin transgene as well as iron deficiency.

Authors

Usage

Running on new respublica by: snakemake --latency-wait 10 -j 10 -p -c "sbatch --job-name={params.jobName} --mem={params.mem} -c {threads} --time=360 -e sbatch/{params.jobName}.e -o sbatch/{params.jobName}.o"

Workflow

alt text

Code Snippets

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shell:
  '''
  conda activate qiime2-2019.7
  #1
  qiime aldex2 aldex2 \
      --i-table {input.table_differentials_transgene_gastric_PicoLab_Rodent_Diet} \
      --m-metadata-file {input.metadata_differentials_transgene_gastric_PicoLab_Rodent_Diet} \
      --m-metadata-column Mouse_background \
      --o-differentials {output.differentials_transgene_gastric_PicoLab_Rodent_Diet} \
      --verbose &> {log}
  qiime aldex2 effect-plot \
      --i-table {output.differentials_transgene_gastric_PicoLab_Rodent_Diet} \
      --o-visualization {output.differentials_transgene_gastric_PicoLab_Rodent_Diet_viz} &>> {log}
  qiime aldex2 extract-differences \
      --i-table {output.differentials_transgene_gastric_PicoLab_Rodent_Diet} \
      --o-differentials {output.differentials_transgene_gastric_PicoLab_Rodent_Diet_sig} \
      --p-sig-threshold 0.1 \
      --p-effect-threshold 0 \
      --p-difference-threshold 0 &>> {log}    
  #2
  qiime aldex2 aldex2 \
      --i-table {input.table_differentials_transgene_fecal_PicoLab_Rodent_Diet} \
      --m-metadata-file {input.metadata_differentials_transgene_fecal_PicoLab_Rodent_Diet} \
      --m-metadata-column Mouse_background \
      --o-differentials {output.differentials_transgene_fecal_PicoLab_Rodent_Diet} \
      --verbose &>> {log}
  qiime aldex2 effect-plot \
      --i-table {output.differentials_transgene_fecal_PicoLab_Rodent_Diet} \
      --o-visualization {output.differentials_transgene_fecal_PicoLab_Rodent_Diet_viz} &>> {log}
  qiime aldex2 extract-differences \
      --i-table {output.differentials_transgene_fecal_PicoLab_Rodent_Diet} \
      --o-differentials {output.differentials_transgene_fecal_PicoLab_Rodent_Diet_sig} \
      --p-sig-threshold 0.1 \
      --p-effect-threshold 0 \
      --p-difference-threshold 0 &>> {log}    
  #3
  qiime aldex2 aldex2 \
      --i-table {input.table_differentials_iron_deficiency_gastric} \
      --m-metadata-file {input.metadata_differentials_iron_deficiency_gastric} \
      --m-metadata-column Diet_Or_Water_treatment \
      --o-differentials {output.differentials_iron_deficiency_gastric} \
      --verbose &>> {log}
  qiime aldex2 effect-plot \
      --i-table {output.differentials_iron_deficiency_gastric} \
      --o-visualization {output.differentials_iron_deficiency_gastric_viz} &>> {log}
  qiime aldex2 extract-differences \
      --i-table {output.differentials_iron_deficiency_gastric} \
      --o-differentials {output.differentials_iron_deficiency_gastric_sig} \
      --p-sig-threshold 0.1 \
      --p-effect-threshold 0 \
      --p-difference-threshold 0 &>> {log}
  #4
  qiime aldex2 aldex2 \
      --i-table {input.table_differentials_iron_deficiency_fecal} \
      --m-metadata-file {input.metadata_differentials_iron_deficiency_fecal} \
      --m-metadata-column Diet_Or_Water_treatment \
      --o-differentials {output.differentials_iron_deficiency_fecal} \
      --verbose &>> {log}
  qiime aldex2 effect-plot \
      --i-table {output.differentials_iron_deficiency_fecal} \
      --o-visualization {output.differentials_iron_deficiency_fecal_viz} &>> {log}
  qiime aldex2 extract-differences \
      --i-table {output.differentials_iron_deficiency_fecal} \
      --o-differentials {output.differentials_iron_deficiency_fecal_sig} \
      --p-sig-threshold 0.1 \
      --p-effect-threshold 0 \
      --p-difference-threshold 0 &>> {log}  
  #5
  qiime aldex2 aldex2 \
      --i-table {input.table_differentials_DCA_gastric_uninfected} \
      --m-metadata-file {input.metadata_differentials_DCA_gastric_uninfected} \
      --m-metadata-column Diet_Or_Water_treatment \
      --o-differentials {output.differentials_DCA_gastric_uninfected} \
      --verbose &>> {log}
  qiime aldex2 effect-plot \
      --i-table {output.differentials_DCA_gastric_uninfected} \
      --o-visualization {output.differentials_DCA_gastric_uninfected_viz} &>> {log}
  qiime aldex2 extract-differences \
      --i-table {output.differentials_DCA_gastric_uninfected} \
      --o-differentials {output.differentials_DCA_gastric_uninfected_sig} \
      --p-sig-threshold 0.25 \
      --p-effect-threshold 0 \
      --p-difference-threshold 0 &>> {log}  
  #6
  qiime aldex2 aldex2 \
      --i-table {input.table_differentials_DCA_fecal_uninfected} \
      --m-metadata-file {input.metadata_differentials_DCA_fecal_uninfected} \
      --m-metadata-column Diet_Or_Water_treatment \
      --o-differentials {output.differentials_DCA_fecal_uninfected} \
      --verbose &>> {log}
  qiime aldex2 effect-plot \
      --i-table {output.differentials_DCA_fecal_uninfected} \
      --o-visualization {output.differentials_DCA_fecal_uninfected_viz} &>> {log}
  qiime aldex2 extract-differences \
      --i-table {output.differentials_DCA_fecal_uninfected} \
      --o-differentials {output.differentials_DCA_fecal_uninfected_sig} \
      --p-sig-threshold 0.5 \
      --p-effect-threshold 0 \
      --p-difference-threshold 0 &>> {log} 
  #7
  qiime aldex2 aldex2 \
      --i-table {input.table_differentials_infection_gastric_H20} \
      --m-metadata-file {input.metadata_differentials_infection_gastric_H20} \
      --m-metadata-column Infection \
      --o-differentials {output.differentials_infection_gastric_H20} \
      --verbose &>> {log}
  qiime aldex2 effect-plot \
      --i-table {output.differentials_infection_gastric_H20} \
      --o-visualization {output.differentials_infection_gastric_H20_viz} &>> {log}
  qiime aldex2 extract-differences \
      --i-table {output.differentials_infection_gastric_H20} \
      --o-differentials {output.differentials_infection_gastric_H20_sig} \
      --p-sig-threshold 1 \
      --p-effect-threshold 0 \
      --p-difference-threshold 0 &>> {log}
  #8
  qiime aldex2 aldex2 \
      --i-table {input.table_differentials_infection_gastric_DCA} \
      --m-metadata-file {input.metadata_differentials_infection_gastric_DCA} \
      --m-metadata-column Infection \
      --o-differentials {output.differentials_infection_gastric_DCA} \
      --verbose &>> {log}
  qiime aldex2 effect-plot \
      --i-table {output.differentials_infection_gastric_DCA} \
      --o-visualization {output.differentials_infection_gastric_DCA_viz} &>> {log}
  qiime aldex2 extract-differences \
      --i-table {output.differentials_infection_gastric_DCA} \
      --o-differentials {output.differentials_infection_gastric_DCA_sig} \
      --p-sig-threshold 0.25 \
      --p-effect-threshold 0 \
      --p-difference-threshold 0 &>> {log} 
  #9
  qiime aldex2 aldex2 \
      --i-table {input.table_differentials_infection_fecal_H20} \
      --m-metadata-file {input.metadata_differentials_infection_fecal_H20} \
      --m-metadata-column Infection \
      --o-differentials {output.differentials_infection_fecal_H20} \
      --verbose &>> {log}
  qiime aldex2 effect-plot \
      --i-table {output.differentials_infection_fecal_H20} \
      --o-visualization {output.differentials_infection_fecal_H20_viz} &>> {log}
  qiime aldex2 extract-differences \
      --i-table {output.differentials_infection_fecal_H20} \
      --o-differentials {output.differentials_infection_fecal_H20_sig} \
      --p-sig-threshold 0.25 \
      --p-effect-threshold 0 \
      --p-difference-threshold 0 &>> {log} 
  #10
  qiime aldex2 aldex2 \
      --i-table {input.table_differentials_infection_fecal_DCA} \
      --m-metadata-file {input.metadata_differentials_infection_fecal_DCA} \
      --m-metadata-column Infection \
      --o-differentials {output.differentials_infection_fecal_DCA} \
      --verbose &>> {log}
  qiime aldex2 effect-plot \
      --i-table {output.differentials_infection_fecal_DCA} \
      --o-visualization {output.differentials_infection_fecal_DCA_viz} &>> {log}
  qiime aldex2 extract-differences \
      --i-table {output.differentials_infection_fecal_DCA} \
      --o-differentials {output.differentials_infection_fecal_DCA_sig} \
      --p-sig-threshold 0.25 \
      --p-effect-threshold 0 \
      --p-difference-threshold 0 &>> {log}
  #11
  qiime aldex2 aldex2 \
      --i-table {input.table_differentials_4groups_gastric} \
      --m-metadata-file {input.metadata_differentials_4groups_gastric} \
      --m-metadata-column Diet_Or_Water_treatment \
      --o-differentials {output.differentials_4groups_gastric} \
      --verbose &>> {log}
  qiime aldex2 effect-plot \
      --i-table {output.differentials_4groups_gastric} \
      --o-visualization {output.differentials_4groups_gastric_viz} &>> {log}
  qiime aldex2 extract-differences \
      --i-table {output.differentials_4groups_gastric} \
      --o-differentials {output.differentials_4groups_gastric_sig} \
      --p-sig-threshold 1 \
      --p-effect-threshold 0 \
      --p-difference-threshold 0 &>> {log} 
  #12
  qiime aldex2 aldex2 \
      --i-table {input.table_differentials_4groups_fecal} \
      --m-metadata-file {input.metadata_differentials_4groups_fecal} \
      --m-metadata-column Diet_Or_Water_treatment \
      --o-differentials {output.differentials_4groups_fecal} \
      --verbose &>> {log}
  qiime aldex2 effect-plot \
      --i-table {output.differentials_4groups_fecal} \
      --o-visualization {output.differentials_4groups_fecal_viz} &>> {log}
  qiime aldex2 extract-differences \
      --i-table {output.differentials_4groups_fecal} \
      --o-differentials {output.differentials_4groups_fecal_sig} \
      --p-sig-threshold 0.25 \
      --p-effect-threshold 0 \
      --p-difference-threshold 0 &>> {log} 

  conda deactivate    
  '''
SnakeMake QIIME2.0 From line 71 of rules/aldex2.smk 
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shell:
    '''
    conda activate qiime2-2019.7

    # collapse to asv to taxon
    qiime taxa collapse \
        --i-table {input.table_2k} \
        --i-taxonomy {input.taxonomy} \
        --o-collapsed-table {output.uniform_table} \
        --p-level 7 &> {log} # means that we group at species level

    # filter feature table
    qiime feature-table filter-features \
        --i-table {output.uniform_table} \
        --p-min-frequency {config[min-frequency_all]} \
        --p-min-samples {config[min-samples]} \
        --o-filtered-table {output.filtered_uniform_table} &>> {log}        

    # add a pseudocount to the FeatureTable[Frequency]
    qiime composition add-pseudocount \
        --i-table {output.filtered_uniform_table} \
        --o-composition-table {output.cfu_table} &> {log}

    qiime composition ancom \
        --i-table {output.cfu_table} \
        --m-metadata-file {input.metadata} \
        --m-metadata-column study_group \
        --o-visualization {output.ancom_uniform_study_group} &>> {log}

    qiime composition ancom \
        --i-table {output.cfu_table} \
        --m-metadata-file {input.metadata} \
        --m-metadata-column study_day \
        --o-visualization {output.ancom_uniform_study_day} &>> {log}

    conda deactivate
    '''
SnakeMake QIIME2.0 From line 18 of rules/ANCOM_taxa.smk 
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shell:
    '''
    conda activate qiime2-2019.7
    qiime dada2 denoise-paired \
        --i-demultiplexed-seqs {input.q2_primerRM} \
        --p-trunc-len-f {config[truncation_len-f]} \
        --p-trunc-len-r {config[truncation_len-r]} \
        --p-trim-left-f 0 \
        --p-trim-left-r 0 \
        --p-n-reads-learn {config[training]} \
        --p-n-threads {threads} \
        --p-chimera-method {config[chimera]} \
        --o-table {output.table} \
        --o-representative-sequences {output.seq} \
        --o-denoising-stats {output.stats} --verbose &> {log}
    conda deactivate
    '''
SnakeMake QIIME2.0 From line 14 of rules/dada2_denoise.smk 
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shell:
    '''
    conda activate qiime2-2019.7
    qiime metadata tabulate \
        --m-input-file {input.stats} \
        --o-visualization {output.stats_viz} --verbose &> {log}

    qiime feature-table summarize \
        --i-table {input.table} \
        --o-visualization {output.table_viz} \
        --m-sample-metadata-file {input.stats} --verbose &>> {log}

    qiime feature-table tabulate-seqs \
        --i-data {input.seq} \
        --o-visualization {output.seq_viz} --verbose &>> {log}

    qiime tools export \
        --input-path {input.table} \
        --output-path {params.outdir}/asv-table &>> {log}

    qiime tools export \
        --input-path {input.stats} \
        --output-path {params.outdir}/stats-dada2 &>> {log}

    conda deactivate   
    '''
SnakeMake QIIME2.0 From line 47 of rules/dada2_denoise.smk 
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shell:
    '''
    ##  --p-sampling-depth should be carefully chosen by reviewing the table_summary file -asv-table.qzv

    conda activate qiime2-2019.7
    # echo "this tis to test conda..." &> {log}
    qiime diversity core-metrics-phylogenetic \
        --i-phylogeny {input.rooted_tree} \
        --i-table {input.feature_table} \
        --p-sampling-depth {config[sampling_depth]} \
        --p-n-jobs {threads} \
        --m-metadata-file {input.metadata} \
        --o-rarefied-table {output.rarefied_table} \
        --o-faith-pd-vector {output.faith_pd_vector} \
        --o-observed-otus-vector {output.observed_otus_vector} \
        --o-shannon-vector {output.shannon_vector} \
        --o-evenness-vector {output.evenness_vector} \
        --o-unweighted-unifrac-distance-matrix {output.unweighted_unifrac_distance_matrix} \
        --o-weighted-unifrac-distance-matrix {output.weighted_unifrac_distance_matrix} \
        --o-jaccard-distance-matrix {output.jaccard_distance_matrix} \
        --o-bray-curtis-distance-matrix {output.bray_curtis_distance_matrix} \
        --o-unweighted-unifrac-pcoa-results {output.unweighted_unifrac_pcoa_results} \
        --o-weighted-unifrac-pcoa-results {output.weighted_unifrac_pcoa_results} \
        --o-jaccard-pcoa-results {output.jaccard_pcoa_results} \
        --o-bray-curtis-pcoa-results {output.bray_curtis_pcoa_results} \
        --o-unweighted-unifrac-emperor {output.unweighted_unifrac_emperor} \
        --o-weighted-unifrac-emperor {output.weighted_unifrac_emperor} \
        --o-jaccard-emperor {output.jaccard_emperor} \
        --o-bray-curtis-emperor {output.bray_curtis_emperor} &> {log}

    conda deactivate   
    '''
SnakeMake QIIME2.0 From line 34 of rules/diversity.smk 
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shell:
    '''
    conda activate qiime2-2019.7
    qiime diversity alpha-group-significance \
        --i-alpha-diversity {input.faith_pd_vector}\
        --m-metadata-file {input.metadata} \
        --o-visualization {output.faith_pd_group_significance} &> {log}


    qiime diversity alpha-group-significance \
        --i-alpha-diversity {input.evenness_vector} \
        --m-metadata-file {input.metadata} \
        --o-visualization {output.evenness_group_significance} &>> {log}  

    conda deactivate
    '''
SnakeMake QIIME2.0 From line 81 of rules/diversity.smk 
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shell:
    '''
    conda activate qiime2-2019.7
    qiime diversity beta-group-significance \
        --i-distance-matrix {input.weighted_unifrac_distance_matrix_transgene_gastric_PicoLab_Rodent_Diet} \
        --m-metadata-file {input.metadata_differentials_transgene_gastric_PicoLab_Rodent_Diet} \
        --m-metadata-column Mouse_background \
        --o-visualization {output.weighted_unifrac_significance_transgene_gastric_PicoLab_Rodent_Diet} &>> {log} 

    qiime diversity beta-group-significance \
        --i-distance-matrix {input.weighted_unifrac_distance_matrix_transgene_fecal_PicoLab_Rodent_Diet} \
        --m-metadata-file {input.metadata_differentials_transgene_fecal_PicoLab_Rodent_Diet} \
        --m-metadata-column Mouse_background \
        --o-visualization {output.weighted_unifrac_significance_transgene_fecal_PicoLab_Rodent_Diet} &>> {log} 

    qiime diversity beta-group-significance \
        --i-distance-matrix {input.weighted_unifrac_distance_matrix_iron_deficiency_gastric} \
        --m-metadata-file {input.metadata_differentials_iron_deficiency_gastric} \
        --m-metadata-column Diet_Or_Water_treatment \
        --o-visualization {output.weighted_unifrac_significance_iron_deficiency_gastric} &>> {log}     


    qiime diversity beta-group-significance \
        --i-distance-matrix {input.weighted_unifrac_distance_matrix_iron_deficiency_fecal} \
        --m-metadata-file {input.metadata_differentials_iron_deficiency_fecal} \
        --m-metadata-column Diet_Or_Water_treatment \
        --o-visualization {output.weighted_unifrac_significance_iron_deficiency_fecal} &>> {log} 

     qiime diversity beta-group-significance \
        --i-distance-matrix {input.weighted_unifrac_distance_matrix_DCA_gastric_uninfected} \
        --m-metadata-file {input.metadata_differentials_DCA_gastric_uninfected} \
        --m-metadata-column Diet_Or_Water_treatment \
        --o-visualization {output.weighted_unifrac_significance_DCA_gastric_uninfected} &>> {log} 

    qiime diversity beta-group-significance \
        --i-distance-matrix {input.weighted_unifrac_distance_matrix_DCA_fecal_uninfected} \
        --m-metadata-file {input.metadata_differentials_DCA_fecal_uninfected} \
        --m-metadata-column Diet_Or_Water_treatment \
        --o-visualization {output.weighted_unifrac_significance_DCA_fecal_uninfected} &>> {log} 

    qiime diversity beta-group-significance \
        --i-distance-matrix {input.weighted_unifrac_distance_matrix_infection_gastric_H20} \
        --m-metadata-file {input.metadata_differentials_infection_gastric_H20} \
        --m-metadata-column Infection \
        --o-visualization {output.weighted_unifrac_significance_infection_gastric_H20} &>> {log} 

    qiime diversity beta-group-significance \
        --i-distance-matrix {input.weighted_unifrac_distance_matrix_infection_gastric_DCA} \
        --m-metadata-file {input.metadata_differentials_infection_gastric_DCA} \
        --m-metadata-column Infection \
        --o-visualization {output.weighted_unifrac_significance_infection_gastric_DCA} &>> {log} 

    qiime diversity beta-group-significance \
        --i-distance-matrix {input.weighted_unifrac_distance_matrix_infection_fecal_H20} \
        --m-metadata-file {input.metadata_differentials_infection_fecal_H20} \
        --m-metadata-column Infection \
        --o-visualization {output.weighted_unifrac_significance_infection_fecal_H20} &>> {log} 

    qiime diversity beta-group-significance \
        --i-distance-matrix {input.weighted_unifrac_distance_matrix_infection_fecal_DCA} \
        --m-metadata-file {input.metadata_differentials_infection_fecal_DCA} \
        --m-metadata-column Infection \
        --o-visualization {output.weighted_unifrac_significance_infection_fecal_DCA} &>> {log}             

         conda deactivate
    '''
SnakeMake QIIME2.0 From line 138 of rules/diversity.smk 
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shell:
    '''
    conda activate qiime2-2019.7

    qiime diversity filter-distance-matrix \
        --i-distance-matrix {input.weighted_unifrac_distance_matrix} \
        --m-metadata-file {input.metadata_differentials_transgene_gastric_PicoLab_Rodent_Diet} \
        --p-where "[Sample_type]='gastric tissue' AND [Diet_Or_Water_treatment] LIKE 'PicoLab Rodent Diet%'" \
        --o-filtered-distance-matrix {output.weighted_unifrac_distance_matrix_transgene_gastric_PicoLab_Rodent_Diet} &> {log}

    qiime diversity filter-distance-matrix \
        --i-distance-matrix {input.weighted_unifrac_distance_matrix} \
        --m-metadata-file {input.metadata_differentials_transgene_fecal_PicoLab_Rodent_Diet} \
        --p-where "[Sample_type]='fecal pellet' AND [Diet_Or_Water_treatment] LIKE 'PicoLab Rodent Diet%'" \
        --o-filtered-distance-matrix {output.weighted_unifrac_distance_matrix_transgene_fecal_PicoLab_Rodent_Diet} &>> {log}

    qiime diversity filter-distance-matrix \
        --i-distance-matrix {input.weighted_unifrac_distance_matrix} \
        --m-metadata-file {input.metadata_differentials_iron_deficiency_gastric} \
        --p-where "[Sample_type]='gastric tissue' AND [Diet_Or_Water_treatment] LIKE 'TestDiet%'" \
        --o-filtered-distance-matrix {output.weighted_unifrac_distance_matrix_iron_deficiency_gastric} &>> {log}

    qiime diversity filter-distance-matrix \
        --i-distance-matrix {input.weighted_unifrac_distance_matrix} \
        --m-metadata-file {input.metadata_differentials_iron_deficiency_fecal} \
        --p-where "[Sample_type]='fecal pellet' AND [Diet_Or_Water_treatment] LIKE 'TestDiet%'" \
        --o-filtered-distance-matrix {output.weighted_unifrac_distance_matrix_iron_deficiency_fecal} &>> {log}

    qiime diversity filter-distance-matrix \
        --i-distance-matrix {input.weighted_unifrac_distance_matrix} \
        --m-metadata-file {input.metadata_differentials_DCA_gastric_uninfected} \
        --p-where "[Sample_type]='gastric tissue' AND [Diet_Or_Water_treatment] LIKE '%H20%' AND [Infection]='Uninfected'" \
        --o-filtered-distance-matrix {output.weighted_unifrac_distance_matrix_DCA_gastric_uninfected} &>> {log}

    qiime diversity filter-distance-matrix \
        --i-distance-matrix {input.weighted_unifrac_distance_matrix} \
        --m-metadata-file {input.metadata_differentials_DCA_fecal_uninfected} \
        --p-where "[Sample_type]='fecal pellet' AND [Diet_Or_Water_treatment] LIKE '%H20%' AND [Infection]='Uninfected'" \
        --o-filtered-distance-matrix {output.weighted_unifrac_distance_matrix_DCA_fecal_uninfected} &>> {log}

    qiime diversity filter-distance-matrix \
        --i-distance-matrix {input.weighted_unifrac_distance_matrix} \
        --m-metadata-file {input.metadata_differentials_infection_gastric_H20} \
        --p-where "[Sample_type]='gastric tissue' AND [Diet_Or_Water_treatment] LIKE 'H20%'" \
        --o-filtered-distance-matrix {output.weighted_unifrac_distance_matrix_infection_gastric_H20} &>> {log}     

    qiime diversity filter-distance-matrix \
        --i-distance-matrix {input.weighted_unifrac_distance_matrix} \
        --m-metadata-file {input.metadata_differentials_infection_gastric_DCA} \
        --p-where "[Sample_type]='gastric tissue' AND [Diet_Or_Water_treatment] LIKE '%DCA%'" \
        --o-filtered-distance-matrix {output.weighted_unifrac_distance_matrix_infection_gastric_DCA} &>> {log}

    qiime diversity filter-distance-matrix \
        --i-distance-matrix {input.weighted_unifrac_distance_matrix} \
        --m-metadata-file {input.metadata_differentials_infection_fecal_H20} \
        --p-where "[Sample_type]='fecal pellet' AND [Diet_Or_Water_treatment] LIKE 'H20%'" \
        --o-filtered-distance-matrix {output.weighted_unifrac_distance_matrix_infection_fecal_H20} &>> {log}         

    qiime diversity filter-distance-matrix \
        --i-distance-matrix {input.weighted_unifrac_distance_matrix} \
        --m-metadata-file {input.metadata_differentials_infection_fecal_DCA} \
        --p-where "[Sample_type]='fecal pellet' AND [Diet_Or_Water_treatment] LIKE '%DCA%'" \
        --o-filtered-distance-matrix {output.weighted_unifrac_distance_matrix_infection_fecal_DCA} &>> {log}  

    conda deactivate
    '''
SnakeMake QIIME2.0 From line 35 of rules/filter_distance_matrix.smk 
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shell:
    '''
    conda activate qiime2-2019.7

    qiime feature-table filter-samples \
        --i-table {input.table} \
        --m-metadata-file {input.metadata_differentials_transgene_gastric_PicoLab_Rodent_Diet} \
        --p-where "[Sample_type]='gastric tissue' AND [Diet_Or_Water_treatment] LIKE 'PicoLab Rodent Diet%'" \
        --o-filtered-table {output.table_differentials_transgene_gastric_PicoLab_Rodent_Diet} &> {log}

    qiime feature-table filter-samples \
        --i-table {input.table} \
        --m-metadata-file {input.metadata_differentials_transgene_fecal_PicoLab_Rodent_Diet} \
        --p-where "[Sample_type]='fecal pellet' AND [Diet_Or_Water_treatment] LIKE 'PicoLab Rodent Diet%'" \
        --o-filtered-table {output.table_differentials_transgene_fecal_PicoLab_Rodent_Diet} &>> {log}

    qiime feature-table filter-samples \
        --i-table {input.table} \
        --m-metadata-file {input.metadata_differentials_iron_deficiency_gastric} \
        --p-where "[Sample_type]='gastric tissue' AND [Diet_Or_Water_treatment] LIKE 'TestDiet%'" \
        --o-filtered-table {output.table_differentials_iron_deficiency_gastric} &>> {log}

    qiime feature-table filter-samples \
        --i-table {input.table} \
        --m-metadata-file {input.metadata_differentials_iron_deficiency_fecal} \
        --p-where "[Sample_type]='fecal pellet' AND [Diet_Or_Water_treatment] LIKE 'TestDiet%'" \
        --o-filtered-table {output.table_differentials_iron_deficiency_fecal} &>> {log}

    qiime feature-table filter-samples \
        --i-table {input.table} \
        --m-metadata-file {input.metadata_differentials_DCA_gastric_uninfected} \
        --p-where "[Sample_type]='gastric tissue' AND [Diet_Or_Water_treatment] LIKE '%H20%' AND [Infection]='Uninfected'" \
        --o-filtered-table {output.table_differentials_DCA_gastric_uninfected} &>> {log}

    qiime feature-table filter-samples \
        --i-table {input.table} \
        --m-metadata-file {input.metadata_differentials_DCA_fecal_uninfected} \
        --p-where "[Sample_type]='fecal pellet' AND [Diet_Or_Water_treatment] LIKE '%H20%' AND [Infection]='Uninfected'" \
        --o-filtered-table {output.table_differentials_DCA_fecal_uninfected} &>> {log}

    qiime feature-table filter-samples \
        --i-table {input.table} \
        --m-metadata-file {input.metadata_differentials_infection_gastric_H20} \
        --p-where "[Sample_type]='gastric tissue' AND [Diet_Or_Water_treatment] LIKE 'H20%'" \
        --o-filtered-table {output.table_differentials_infection_gastric_H20} &>> {log}     

    qiime feature-table filter-samples \
        --i-table {input.table} \
        --m-metadata-file {input.metadata_differentials_infection_gastric_DCA} \
        --p-where "[Sample_type]='gastric tissue' AND [Diet_Or_Water_treatment] LIKE '%DCA%'" \
        --o-filtered-table {output.table_differentials_infection_gastric_DCA} &>> {log}

    qiime feature-table filter-samples \
        --i-table {input.table} \
        --m-metadata-file {input.metadata_differentials_infection_fecal_H20} \
        --p-where "[Sample_type]='fecal pellet' AND [Diet_Or_Water_treatment] LIKE 'H20%'" \
        --o-filtered-table {output.table_differentials_infection_fecal_H20} &>> {log}         

    qiime feature-table filter-samples \
        --i-table {input.table} \
        --m-metadata-file {input.metadata_differentials_infection_fecal_DCA} \
        --p-where "[Sample_type]='fecal pellet' AND [Diet_Or_Water_treatment] LIKE '%DCA%'" \
        --o-filtered-table {output.table_differentials_infection_fecal_DCA} &>> {log}  

    qiime feature-table filter-samples \
        --i-table {input.table} \
        --m-metadata-file {input.metadata_differentials_4groups_gastric} \
        --p-where "[Sample_type]='gastric tissue' AND [Diet_Or_Water_treatment] LIKE '%H20%'" \
        --o-filtered-table {output.table_differentials_4groups_gastric} &>> {log}  

    qiime feature-table filter-samples \
        --i-table {input.table} \
        --m-metadata-file {input.metadata_differentials_4groups_fecal} \
        --p-where "[Sample_type]='fecal pellet' AND [Diet_Or_Water_treatment] LIKE '%H20%'" \
        --o-filtered-table {output.table_differentials_4groups_fecal} &>> {log}  

    conda deactivate
    '''
SnakeMake QIIME2.0 From line 36 of rules/filter.smk 
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shell:
    '''
    conda activate qiime2-2019.7
    qiime phylogeny align-to-tree-mafft-fasttree \
        --p-n-threads {threads} \
        --i-sequences {input.seq} \
        --o-alignment {output.alignment} \
        --o-masked-alignment {output.masked_alignment} \
        --o-tree {output.unrooted_tree} \
        --o-rooted-tree {output.rooted_tree} \
        --verbose &> {log}

    conda deactivate   
    '''
SnakeMake QIIME2.0 From line 16 of rules/phylogeny.smk 
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shell:
  "fastqc --quiet -t {threads} --outdir ../results/fastqc {input} &> {log}"
SnakeMake FastQC From line 13 of rules/qc_trim_qc.smk 
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shell:
    '''  
      trimmomatic PE -threads {threads} -phred33 -quiet {input.r1} {input.r2} \
      {output.r1} {output.r1_unpaired} {output.r2} {output.r2_unpaired} {params.trimmer}
    '''
SnakeMake Trimmomatic From line 33 of rules/qc_trim_qc.smk 
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shell:
  "fastqc --quiet -t {threads} --outdir ../results/fastqc_trim {input} &> {log}"
SnakeMake FastQC From line 51 of rules/qc_trim_qc.smk 
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shell: 
  """
  multiqc --force --quiet --filename multiqc.html --outdir ../results/raw_multi_fastqc {input.raw_qc} &> {log} #run multiqc
  # repeat for trimmed data
  multiqc --force --quiet --filename multiqc.html --outdir ../results/trim_multi_fastqc {input.trim_qc} &>> {log} #run multiqc
  """
SnakeMake MultiQC From line 67 of rules/qc_trim_qc.smk 
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shell:
    '''
    # Imports demultiplexed paired end FASTQ files
    # Needed to create a unique manifest file to map file paths to sample ids
    qiime tools import \
    --type 'SampleData[PairedEndSequencesWithQuality]' \
    --input-path {input} \
    --input-format PairedEndFastqManifestPhred33V2 \
    --output-path {output.q2_import} &> {log}
    '''
SnakeMake QIIME2.0 From line 15 of rules/qiime2_import.smk 
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shell:
    '''
    qiime cutadapt trim-paired \
        --p-cores {threads} \
        --i-demultiplexed-sequences {input.q2_import} \
        --p-front-f {config[primerF]} \
        --p-front-r {config[primerR]} \
        --p-error-rate {config[primer_err]} \
        --p-overlap {config[primer_overlap]} \
        --p-match-read-wildcards \
        --p-match-adapter-wildcards \
        --o-trimmed-sequences {output.q2_primerRM} &> {log}

    qiime demux summarize \
        --i-data {input.q2_import} \
        --o-visualization {output.q2_raw_viz} &>> {log}    

    qiime demux summarize \
        --i-data {output.q2_primerRM} \
        --o-visualization {output.q2_primerRM_viz} &>> {log}
    '''
SnakeMake Cutadapt QIIME2.0 From line 14 of rules/rm_primers.smk 
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shell:
  '''
  conda activate qiime2-2019.7
  qiime feature-classifier classify-sklearn \
      --i-classifier {input.classifier} \
      --i-reads {input.seq} \
      --o-classification {output.taxonomy} &> {log}
  conda deactivate    
  '''
SnakeMake QIIME2.0 From line 19 of rules/taxonomy.smk 
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shell:
  '''
  qiime metadata tabulate \
    --m-input-file {input.taxonomy} \
    --o-visualization {output.taxonomy_viz} &> {log}

  qiime tools export \
    --input-path {input.taxonomy} \
    --output-path {params.outdir} &>> {log}

  qiime taxa barplot \
    --i-table {input.feature_table} \
    --i-taxonomy {input.taxonomy} \
    --m-metadata-file {input.metadata} \
    --o-visualization {output.taxa_barplot_viz} &>> {log}  
  '''
SnakeMake QIIME2.0 From line 43 of rules/taxonomy.smk
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Created: 1yr ago
Updated: 1yr ago
Maitainers: public
URL: https://github.com/chaodi51/16S_rRNAseq_gastric
Name: 16s_rrnaseq_gastric
Version: 1
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Copyright: Public Domain
License: MIT License
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