DiffEnrich Analysis Tutorial - Multiple Interface Edition

Introduction

In this tutorial you’ll use QIIME 2 to perform an analysis of some data.

Typical Run Time: 12 Minutes

Description

This guide is a preview of how you can use q2-autopepsirf’s diffEnrich module, along with how to use the individual modules of q2-pepsirf and q2-ps-plot to accomplish a diffEnrich analysis.

Sample Raw Data

Before starting the analysis, download the raw data and bin files. These IM0032-pA_PV1_subset.qza, pA_PV1.5_r1bins_IM25-26.qza, and samples_source.tsv files are used throughout the rest of the tutorial.

from qiime2 import Artifact
from qiime2 import Metadata
from urllib import request

url = 'https://ladnerlab.github.io/pepsirf-q2-plugin-docs/data/tutorials/pepsirf-tutorial/IM0032-pA-PV1-subset.qza'
fn = 'IM0032-pA-PV1-subset.qza'
request.urlretrieve(url, fn)
IM0032_pA_PV1_subset = Artifact.load(fn)

url = 'https://ladnerlab.github.io/pepsirf-q2-plugin-docs/data/tutorials/pepsirf-tutorial/pA-PV1.5-r1bins-IM25-26.qza'
fn = 'pA-PV1.5-r1bins-IM25-26.qza'
request.urlretrieve(url, fn)
pA_PV1_5_r1bins_IM25_26 = Artifact.load(fn)

url = 'https://ladnerlab.github.io/pepsirf-q2-plugin-docs/data/tutorials/pepsirf-tutorial/samples-source.tsv'
fn = 'samples-source.tsv'
request.urlretrieve(url, fn)
samples_source_md = Metadata.load(fn)

library(reticulate)

Artifact <- import("qiime2")$Artifact
Metadata <- import("qiime2")$Metadata
request <- import("urllib")$request

url <- 'https://ladnerlab.github.io/pepsirf-q2-plugin-docs/data/tutorials/pepsirf-tutorial/IM0032-pA-PV1-subset.qza'
fn <- 'IM0032-pA-PV1-subset.qza'
request$urlretrieve(url, fn)
IM0032_pA_PV1_subset <- Artifact$load(fn)

url <- 'https://ladnerlab.github.io/pepsirf-q2-plugin-docs/data/tutorials/pepsirf-tutorial/pA-PV1.5-r1bins-IM25-26.qza'
fn <- 'pA-PV1.5-r1bins-IM25-26.qza'
request$urlretrieve(url, fn)
pA_PV1_5_r1bins_IM25_26 <- Artifact$load(fn)

url <- 'https://ladnerlab.github.io/pepsirf-q2-plugin-docs/data/tutorials/pepsirf-tutorial/samples-source.tsv'
fn <- 'samples-source.tsv'
request$urlretrieve(url, fn)
samples_source_md <- Metadata$load(fn)

wget \
  -O 'IM0032-pA-PV1-subset.qza' \
  'https://ladnerlab.github.io/pepsirf-q2-plugin-docs/data/tutorials/pepsirf-tutorial/IM0032-pA-PV1-subset.qza'

wget \
  -O 'pA-PV1.5-r1bins-IM25-26.qza' \
  'https://ladnerlab.github.io/pepsirf-q2-plugin-docs/data/tutorials/pepsirf-tutorial/pA-PV1.5-r1bins-IM25-26.qza'

wget \
  -O 'samples-source.tsv' \
  'https://ladnerlab.github.io/pepsirf-q2-plugin-docs/data/tutorials/pepsirf-tutorial/samples-source.tsv'

def raw_factory():
   import qiime2
   return qiime2.Artifact.load("source/data/IM0032-pA_PV1_subset.qza")

raw_data = use.init_artifact("IM0032-pA_PV1_subset", raw_factory)

def bin_factory():
   import qiime2
   return qiime2.Artifact.load("source/data/pA_PV1.5_r1bins_IM25-26.qza")

bin_data = use.init_artifact("pA_PV1.5_r1bins_IM25-26", bin_factory)

def metadata_factory():
   import qiime2
   return qiime2.Metadata.load("source/data/samples_source.tsv")

metadata = use.init_metadata('samples_source', metadata_factory)
Using the Upload Data tool:

  1. On the first tab (Regular), press the Paste/Fetch data button at the bottom.

    1. Set “Name” (first text-field) to: IM0032-pA-PV1-subset.qza

    2. In the larger text-area, copy-and-paste: https://ladnerlab.github.io/pepsirf-q2-plugin-docs/data/tutorials/pepsirf-tutorial/IM0032-pA-PV1-subset.qza

    3. (“Type”, “Genome”, and “Settings” can be ignored)

  2. Press the Start button at the bottom.

Using the Upload Data tool:

  1. On the first tab (Regular), press the Paste/Fetch data button at the bottom.

    1. Set “Name” (first text-field) to: pA-PV1.5-r1bins-IM25-26.qza

    2. In the larger text-area, copy-and-paste: https://ladnerlab.github.io/pepsirf-q2-plugin-docs/data/tutorials/pepsirf-tutorial/pA-PV1.5-r1bins-IM25-26.qza

    3. (“Type”, “Genome”, and “Settings” can be ignored)

  2. Press the Start button at the bottom.

Using the Upload Data tool:

  1. On the first tab (Regular), press the Paste/Fetch data button at the bottom.

    1. Set “Name” (first text-field) to: samples-source.tsv

    2. In the larger text-area, copy-and-paste: https://ladnerlab.github.io/pepsirf-q2-plugin-docs/data/tutorials/pepsirf-tutorial/samples-source.tsv

    3. (“Type”, “Genome”, and “Settings” can be ignored)

  2. Press the Start button at the bottom.

All data that is used as input to QIIME 2 is in form of QIIME 2 artifacts, which contain information about the type of data and the source of the data.

Autopepsirf Automation

Once you have downloaded the file, you can automatically run q2-pepsirf and q2-ps-plot with q2-autopepsirf. This can be done by running the following command (replace pepsirf_binary with how you call pepsirf on your machine):

import qiime2.plugins.autopepsirf.actions as autopepsirf_actions

action_results = autopepsirf_actions.diffEnrich(
    raw_data=IM0032_pA_PV1_subset,
    bins=pA_PV1_5_r1bins_IM25_26,
    negative_id='SB_',
    exact_z_thresh='6,10',
    pepsirf_tsv_dir='./testingTSV',
    tsv_base_str='IM0032-pA_PV1_subset',
    hdi=0.95,
    pepsirf_binary='/home/runner/work/pepsirf-q2-plugin-docs/pepsirf-q2-plugin-docs/pepsirf',
)
colsum = action_results.col_sum
diff = action_results.diff
diff_ratio = action_results.diff_ratio
zscore = action_results.zscore
zscore_nan = action_results.zscore_nan
sample_names = action_results.sample_names
read_counts = action_results.read_counts
rcBoxplot_viz = action_results.rc_boxplot
enrich = action_results.enrich
enrichBoxplot_viz = action_results.enrich_count_boxplot
zScatter_viz = action_results.zscore_scatter
csScatter_viz = action_results.colsum_scatter
zenrich_viz = action_results.zenrich_scatter

autopepsirf_actions <- import("qiime2.plugins.autopepsirf.actions")

action_results <- autopepsirf_actions$diffEnrich(
    raw_data=IM0032_pA_PV1_subset,
    bins=pA_PV1_5_r1bins_IM25_26,
    negative_id='SB_',
    exact_z_thresh='6,10',
    pepsirf_tsv_dir='./testingTSV',
    tsv_base_str='IM0032-pA_PV1_subset',
    hdi=0.95,
    pepsirf_binary='/home/runner/work/pepsirf-q2-plugin-docs/pepsirf-q2-plugin-docs/pepsirf',
)
colsum <- action_results$col_sum
diff <- action_results$diff
diff_ratio <- action_results$diff_ratio
zscore <- action_results$zscore
zscore_nan <- action_results$zscore_nan
sample_names <- action_results$sample_names
read_counts <- action_results$read_counts
rcBoxplot_viz <- action_results$rc_boxplot
enrich <- action_results$enrich
enrichBoxplot_viz <- action_results$enrich_count_boxplot
zScatter_viz <- action_results$zscore_scatter
csScatter_viz <- action_results$colsum_scatter
zenrich_viz <- action_results$zenrich_scatter

qiime autopepsirf diffEnrich \
  --i-raw-data IM0032-pA-PV1-subset.qza \
  --i-bins pA-PV1.5-r1bins-IM25-26.qza \
  --p-negative-id SB_ \
  --p-exact-z-thresh 6,10 \
  --p-pepsirf-tsv-dir ./testingTSV \
  --p-tsv-base-str IM0032-pA_PV1_subset \
  --p-hdi 0.95 \
  --p-pepsirf-binary /home/runner/work/pepsirf-q2-plugin-docs/pepsirf-q2-plugin-docs/pepsirf \
  --output-dir autopepsirf-diffEnrich

col_sum, diff, diff_ratio, zscore, zscore_nan, sample_names, read_counts, rcBoxplot, enriched, enrichBoxplot, zScatter, csScatter, zenrich = use.action(
use.UsageAction(plugin_id='autopepsirf', action_id='diffEnrich'),
use.UsageInputs(
    raw_data = raw_data,
    bins = bin_data,
    negative_id = "SB_",
    exact_z_thresh = "6,10",
    pepsirf_tsv_dir = "./testingTSV",
    tsv_base_str = "IM0032-pA_PV1_subset",
    hdi = 0.95,
    pepsirf_binary = "/home/runner/work/pepsirf-q2-plugin-docs/pepsirf-q2-plugin-docs/pepsirf"
),
use.UsageOutputNames(
    col_sum = "colsum",
    diff = "diff",
    diff_ratio = "diff_ratio",
    zscore = "zscore",
    zscore_nan = "zscore_nan",
    sample_names = "sample_names",
    read_counts = "read_counts",
    rc_boxplot = "rcBoxplot",
    enrich = "enrich",
    enrich_count_boxplot = "enrichBoxplot",
    zscore_scatter = "zScatter",
    colsum_scatter = "csScatter",
    zenrich_scatter = "zenrich"
)
)
Using the qiime2 autopepsirf diffEnrich tool:

  1. Set “raw_data” to #: IM0032-pA-PV1-subset.qza

  2. Set “bins” to #: pA-PV1.5-r1bins-IM25-26.qza

  3. Expand the additional options section

    1. Set “negative_id” to SB_

    2. Set “exact_z_thresh” to 6,10

    3. Set “pepsirf_tsv_dir” to ./testingTSV

    4. Set “tsv_base_str” to IM0032-pA_PV1_subset

    5. Leave “hdi” as its default value of 0.95

    6. Set “pepsirf_binary” to /home/runner/work/pepsirf-q2-plugin-docs/pepsirf-q2-plugin-docs/pepsirf

  4. Press the Execute button.

Once completed, for each new entry in your history, use the Edit button to set the name as follows:

(Renaming is optional, but it will make any subsequent steps easier to complete.)

History Name

“Name” to set (be sure to press Save)

#: qiime2 autopepsirf diffEnrich [...] : col_sum.qza

colsum.qza

#: qiime2 autopepsirf diffEnrich [...] : diff.qza

diff.qza

#: qiime2 autopepsirf diffEnrich [...] : diff_ratio.qza

diff-ratio.qza

#: qiime2 autopepsirf diffEnrich [...] : zscore.qza

zscore.qza

#: qiime2 autopepsirf diffEnrich [...] : zscore_nan.qza

zscore-nan.qza

#: qiime2 autopepsirf diffEnrich [...] : sample_names.qza

sample-names.qza

#: qiime2 autopepsirf diffEnrich [...] : read_counts.qza

read-counts.qza

#: qiime2 autopepsirf diffEnrich [...] : rc_boxplot.qzv

rcBoxplot.qzv

#: qiime2 autopepsirf diffEnrich [...] : enrich.qza

enrich.qza

#: qiime2 autopepsirf diffEnrich [...] : enrich_count_boxplot.qzv

enrichBoxplot.qzv

#: qiime2 autopepsirf diffEnrich [...] : zscore_scatter.qzv

zScatter.qzv

#: qiime2 autopepsirf diffEnrich [...] : colsum_scatter.qzv

csScatter.qzv

#: qiime2 autopepsirf diffEnrich [...] : zenrich_scatter.qzv

zenrich.qzv

Note

TSV/PNG outputs will not show up on this page. They are just duplicates of the .qza files in a .tsv format.

Pepsirf Normalization

You can also run q2-pepsirf and q2-ps-plot by themseleves to get individual files. Here we wil test q2-pepsirf’s norm module by running the following command (replace pepsirf_binary with how you call pepsirf on your machine):

import qiime2.plugins.pepsirf.actions as pepsirf_actions

IM0032_pA_PV1_subset_CS, = pepsirf_actions.norm(
    peptide_scores=IM0032_pA_PV1_subset,
    pepsirf_binary='/home/runner/work/pepsirf-q2-plugin-docs/pepsirf-q2-plugin-docs/pepsirf',
)

pepsirf_actions <- import("qiime2.plugins.pepsirf.actions")

action_results <- pepsirf_actions$norm(
    peptide_scores=IM0032_pA_PV1_subset,
    pepsirf_binary='/home/runner/work/pepsirf-q2-plugin-docs/pepsirf-q2-plugin-docs/pepsirf',
)
IM0032_pA_PV1_subset_CS <- action_results$qza_output

qiime pepsirf norm \
  --i-peptide-scores IM0032-pA-PV1-subset.qza \
  --p-pepsirf-binary /home/runner/work/pepsirf-q2-plugin-docs/pepsirf-q2-plugin-docs/pepsirf \
  --o-qza-output IM0032-pA-PV1-subset-CS.qza

col_sum, = use.action(
 use.UsageAction(plugin_id='pepsirf', action_id='norm'),
 use.UsageInputs(
     peptide_scores = raw_data,
     pepsirf_binary = "/home/runner/work/pepsirf-q2-plugin-docs/pepsirf-q2-plugin-docs/pepsirf"
 ),
 use.UsageOutputNames(
     qza_output = "IM0032-pA_PV1_subset_CS"
 )
 )
Using the qiime2 pepsirf norm tool:

  1. Set “peptide_scores” to #: IM0032-pA-PV1-subset.qza

  2. Expand the additional options section

    • Set “pepsirf_binary” to /home/runner/work/pepsirf-q2-plugin-docs/pepsirf-q2-plugin-docs/pepsirf

  3. Press the Execute button.

Once completed, for the new entry in your history, use the Edit button to set the name as follows:

(Renaming is optional, but it will make any subsequent steps easier to complete.)

History Name

“Name” to set (be sure to press Save)

#: qiime2 pepsirf norm [...] : qza_output.qza

IM0032-pA-PV1-subset-CS.qza

Pepsirf bin

Here we wil test q2-pepsirf’s bin module by running the following command (replace pepsirf_binary with how you call pepsirf on your machine):

IM0032_pA_PV1_subset_bin, = pepsirf_actions.bin(
    scores=IM0032_pA_PV1_subset_CS,
    bin_size=300,
    round_to=0,
    pepsirf_binary='/home/runner/work/pepsirf-q2-plugin-docs/pepsirf-q2-plugin-docs/pepsirf',
)

action_results <- pepsirf_actions$bin(
    scores=IM0032_pA_PV1_subset_CS,
    bin_size=300L,
    round_to=0L,
    pepsirf_binary='/home/runner/work/pepsirf-q2-plugin-docs/pepsirf-q2-plugin-docs/pepsirf',
)
IM0032_pA_PV1_subset_bin <- action_results$bin_output

qiime pepsirf bin \
  --i-scores IM0032-pA-PV1-subset-CS.qza \
  --p-bin-size 300 \
  --p-round-to 0 \
  --p-pepsirf-binary /home/runner/work/pepsirf-q2-plugin-docs/pepsirf-q2-plugin-docs/pepsirf \
  --o-bin-output IM0032-pA-PV1-subset-bin.qza

pepsirf_bin, = use.action(
 use.UsageAction(plugin_id='pepsirf', action_id='bin'),
 use.UsageInputs(
     scores = col_sum,
     bin_size = 300,
     round_to = 0,
     pepsirf_binary = "/home/runner/work/pepsirf-q2-plugin-docs/pepsirf-q2-plugin-docs/pepsirf"
 ),
 use.UsageOutputNames(
     bin_output = "IM0032-pA_PV1_subset_bin"
 )
 )
Using the qiime2 pepsirf bin tool:

  1. Set “scores” to #: IM0032-pA-PV1-subset-CS.qza

  2. Expand the additional options section

    1. Leave “bin_size” as its default value of 300

    2. Leave “round_to” as its default value of 0

    3. Set “pepsirf_binary” to /home/runner/work/pepsirf-q2-plugin-docs/pepsirf-q2-plugin-docs/pepsirf

  3. Press the Execute button.

Once completed, for the new entry in your history, use the Edit button to set the name as follows:

(Renaming is optional, but it will make any subsequent steps easier to complete.)

History Name

“Name” to set (be sure to press Save)

#: qiime2 pepsirf bin [...] : bin_output.qza

IM0032-pA-PV1-subset-bin.qza

Pepsirf zscore

Here we wil test q2-pepsirf’s zscore module by running the following command (replace pepsirf_binary with how you call pepsirf on your machine):

IM0032_pA_PV1_Z_HDI95, IM0032_pA_PV1_Z_HDI95_nan = pepsirf_actions.zscore(
    scores=diff,
    bins=pA_PV1_5_r1bins_IM25_26,
    hdi=0.95,
    pepsirf_binary='/home/runner/work/pepsirf-q2-plugin-docs/pepsirf-q2-plugin-docs/pepsirf',
)

action_results <- pepsirf_actions$zscore(
    scores=diff,
    bins=pA_PV1_5_r1bins_IM25_26,
    hdi=0.95,
    pepsirf_binary='/home/runner/work/pepsirf-q2-plugin-docs/pepsirf-q2-plugin-docs/pepsirf',
)
IM0032_pA_PV1_Z_HDI95 <- action_results$zscore_output
IM0032_pA_PV1_Z_HDI95_nan <- action_results$nan_report

qiime pepsirf zscore \
  --i-scores autopepsirf-diffEnrich/diff.qza \
  --i-bins pA-PV1.5-r1bins-IM25-26.qza \
  --p-hdi 0.95 \
  --p-pepsirf-binary /home/runner/work/pepsirf-q2-plugin-docs/pepsirf-q2-plugin-docs/pepsirf \
  --o-zscore-output IM0032-pA-PV1-Z-HDI95.qza \
  --o-nan-report IM0032-pA-PV1-Z-HDI95-nan.qza

pepsirf_zscore, pepsirf_nan, = use.action(
 use.UsageAction(plugin_id='pepsirf', action_id='zscore'),
 use.UsageInputs(
     scores = diff,
     bins = bin_data,
     hdi = 0.95,
     pepsirf_binary = "/home/runner/work/pepsirf-q2-plugin-docs/pepsirf-q2-plugin-docs/pepsirf"
     # TODO: maybe store a precompiled pepsirf executable in the PepSIRF repository?
     #pepsirf_binary = "/mnt/c/Users/ANNAB/Documents/GitHub/PepSIRF/precompiled/linux_mint_19.3/pepsirf_1.4.0_linux"
 ),
 use.UsageOutputNames(
     zscore_output = "IM0032-pA_PV1_Z-HDI95",
     nan_report = "IM0032-pA_PV1_Z-HDI95_nan"
 )
 )
Using the qiime2 pepsirf zscore tool:

  1. Set “scores” to #: diff.qza

  2. Set “bins” to #: pA-PV1.5-r1bins-IM25-26.qza

  3. Expand the additional options section

    1. Set “hdi” to 0.95

    2. Set “pepsirf_binary” to /home/runner/work/pepsirf-q2-plugin-docs/pepsirf-q2-plugin-docs/pepsirf

  4. Press the Execute button.

Once completed, for each new entry in your history, use the Edit button to set the name as follows:

(Renaming is optional, but it will make any subsequent steps easier to complete.)

History Name

“Name” to set (be sure to press Save)

#: qiime2 pepsirf zscore [...] : zscore_output.qza

IM0032-pA-PV1-Z-HDI95.qza

#: qiime2 pepsirf zscore [...] : nan_report.qza

IM0032-pA-PV1-Z-HDI95-nan.qza

Pepsirf infoSNPN

Here we wil test q2-pepsirf’s infoSNPN module by running the following command (replace pepsirf_binary with how you call pepsirf on your machine):

IM0032_pA_PV1_SN, = pepsirf_actions.infoSNPN(
    input=IM0032_pA_PV1_subset,
    get='samples',
    pepsirf_binary='/home/runner/work/pepsirf-q2-plugin-docs/pepsirf-q2-plugin-docs/pepsirf',
)

action_results <- pepsirf_actions$infoSNPN(
    input=IM0032_pA_PV1_subset,
    get='samples',
    pepsirf_binary='/home/runner/work/pepsirf-q2-plugin-docs/pepsirf-q2-plugin-docs/pepsirf',
)
IM0032_pA_PV1_SN <- action_results$snpn_output

qiime pepsirf infoSNPN \
  --i-input IM0032-pA-PV1-subset.qza \
  --p-get samples \
  --p-pepsirf-binary /home/runner/work/pepsirf-q2-plugin-docs/pepsirf-q2-plugin-docs/pepsirf \
  --o-snpn-output IM0032-pA-PV1-SN.qza

pepsirf_sample_names, = use.action(
 use.UsageAction(plugin_id='pepsirf', action_id='infoSNPN'),
 use.UsageInputs(
     input = raw_data,
     get = "samples",
     pepsirf_binary = "/home/runner/work/pepsirf-q2-plugin-docs/pepsirf-q2-plugin-docs/pepsirf"
 ),
 use.UsageOutputNames(
     snpn_output = "IM0032-pA_PV1_SN",
 )
 )
Using the qiime2 pepsirf infoSNPN tool:

  1. Set “input” to #: IM0032-pA-PV1-subset.qza

  2. Set “get” to samples

  3. Expand the additional options section

    • Set “pepsirf_binary” to /home/runner/work/pepsirf-q2-plugin-docs/pepsirf-q2-plugin-docs/pepsirf

  4. Press the Execute button.

Once completed, for the new entry in your history, use the Edit button to set the name as follows:

(Renaming is optional, but it will make any subsequent steps easier to complete.)

History Name

“Name” to set (be sure to press Save)

#: qiime2 pepsirf infoSNPN [...] : snpn_output.qza

IM0032-pA-PV1-SN.qza

Pepsirf infoSumOfProbes

Here we wil test q2-pepsirf’s infoSumOfProbes module by running the following command (replace pepsirf_binary with how you call pepsirf on your machine):

IM0032_pA_PV1_RC, = pepsirf_actions.infoSumOfProbes(
    input=IM0032_pA_PV1_subset,
    pepsirf_binary='/home/runner/work/pepsirf-q2-plugin-docs/pepsirf-q2-plugin-docs/pepsirf',
)

action_results <- pepsirf_actions$infoSumOfProbes(
    input=IM0032_pA_PV1_subset,
    pepsirf_binary='/home/runner/work/pepsirf-q2-plugin-docs/pepsirf-q2-plugin-docs/pepsirf',
)
IM0032_pA_PV1_RC <- action_results$sum_of_probes_output

qiime pepsirf infoSumOfProbes \
  --i-input IM0032-pA-PV1-subset.qza \
  --p-pepsirf-binary /home/runner/work/pepsirf-q2-plugin-docs/pepsirf-q2-plugin-docs/pepsirf \
  --o-sum-of-probes-output IM0032-pA-PV1-RC.qza

pepsirf_read_counts, = use.action(
 use.UsageAction(plugin_id='pepsirf', action_id='infoSumOfProbes'),
 use.UsageInputs(
     input = raw_data,
     pepsirf_binary = "/home/runner/work/pepsirf-q2-plugin-docs/pepsirf-q2-plugin-docs/pepsirf"
 ),
 use.UsageOutputNames(
     sum_of_probes_output = "IM0032-pA_PV1_RC",
 )
 )
Using the qiime2 pepsirf infoSumOfProbes tool:

  1. Set “input” to #: IM0032-pA-PV1-subset.qza

  2. Expand the additional options section

    • Set “pepsirf_binary” to /home/runner/work/pepsirf-q2-plugin-docs/pepsirf-q2-plugin-docs/pepsirf

  3. Press the Execute button.

Once completed, for the new entry in your history, use the Edit button to set the name as follows:

(Renaming is optional, but it will make any subsequent steps easier to complete.)

History Name

“Name” to set (be sure to press Save)

#: qiime2 pepsirf infoSumOfProbes [...] : sum_of_probes_output.qza

IM0032-pA-PV1-RC.qza

Pepsirf enrich

Here we wil test q2-pepsirf’s enrich module by running the following command (replace pepsirf_binary with how you call pepsirf on your machine):

samples_col_mdc = samples_source_md.get_column('source')
_6_10Z_HDI95_20CS_300000raw, = pepsirf_actions.enrich(
    source=samples_col_mdc,
    zscores=zscore,
    col_sum=IM0032_pA_PV1_subset_CS,
    exact_z_thresh='6,10',
    exact_cs_thresh='20',
    enrichment_failure=True,
    pepsirf_binary='/home/runner/work/pepsirf-q2-plugin-docs/pepsirf-q2-plugin-docs/pepsirf',
)

samples_col_mdc <- samples_source_md$get_column('source')
action_results <- pepsirf_actions$enrich(
    source=samples_col_mdc,
    zscores=zscore,
    col_sum=IM0032_pA_PV1_subset_CS,
    exact_z_thresh='6,10',
    exact_cs_thresh='20',
    enrichment_failure=TRUE,
    pepsirf_binary='/home/runner/work/pepsirf-q2-plugin-docs/pepsirf-q2-plugin-docs/pepsirf',
)
_6_10Z_HDI95_20CS_300000raw <- action_results$dir_fmt_output

qiime pepsirf enrich \
  --m-source-file samples-source.tsv \
  --m-source-column source \
  --i-zscores autopepsirf-diffEnrich/zscore.qza \
  --i-col-sum IM0032-pA-PV1-subset-CS.qza \
  --p-exact-z-thresh 6,10 \
  --p-exact-cs-thresh 20 \
  --p-enrichment-failure \
  --p-pepsirf-binary /home/runner/work/pepsirf-q2-plugin-docs/pepsirf-q2-plugin-docs/pepsirf \
  --o-dir-fmt-output 6-10Z-HDI95-20CS-300000raw.qza

samples_col = use.get_metadata_column('samples_col', 'source', metadata)

pepsirf_enrich_dir, = use.action(
use.UsageAction(plugin_id='pepsirf', action_id='enrich'),
use.UsageInputs(
    source = samples_col,
    zscores = zscore,
    col_sum = col_sum,
    exact_z_thresh = "6,10",
    exact_cs_thresh = "20",
    enrichment_failure = True,
    pepsirf_binary = "/home/runner/work/pepsirf-q2-plugin-docs/pepsirf-q2-plugin-docs/pepsirf"
),
use.UsageOutputNames(
    dir_fmt_output = "6-10Z-HDI95_20CS_300000raw",
)
)
Using the qiime2 pepsirf enrich tool:

  1. For “source”:

    1. Leave as Metadata from TSV

    2. Set “Metadata Source” to samples-source.tsv

    3. Set “Column Name” to source

  2. Expand the additional options section

    1. Set “zscores” to #: zscore.qza

    2. Set “col_sum” to #: IM0032-pA-PV1-subset-CS.qza

    3. Set “exact_z_thresh” to 6,10

    4. Set “exact_cs_thresh” to 20

    5. Set “enrichment_failure” to Yes

    6. Set “pepsirf_binary” to /home/runner/work/pepsirf-q2-plugin-docs/pepsirf-q2-plugin-docs/pepsirf

  3. Press the Execute button.

Once completed, for the new entry in your history, use the Edit button to set the name as follows:

(Renaming is optional, but it will make any subsequent steps easier to complete.)

History Name

“Name” to set (be sure to press Save)

#: qiime2 pepsirf enrich [...] : dir_fmt_output.qza

6-10Z-HDI95-20CS-300000raw.qza

Ps-plot readCountsBoxplot

Here we will test q2-ps-plot’s readCountsBoxplot module by running the following command:

import qiime2.plugins.ps_plot.actions as ps_plot_actions

RCBoxplot_viz, = ps_plot_actions.readCountsBoxplot(
    read_counts=read_counts,
)

ps_plot_actions <- import("qiime2.plugins.ps_plot.actions")

action_results <- ps_plot_actions$readCountsBoxplot(
    read_counts=read_counts,
)
RCBoxplot_viz <- action_results$visualization

qiime ps-plot readCountsBoxplot \
  --i-read-counts autopepsirf-diffEnrich/read_counts.qza \
  --o-visualization RCBoxplot.qzv

zScatter, = use.action(
 use.UsageAction(plugin_id='ps_plot', action_id='readCountsBoxplot'),
 use.UsageInputs(
     read_counts = read_counts
 ),
 use.UsageOutputNames(
     visualization = "RCBoxplot"
 )
 )
Using the qiime2 ps-plot readCountsBoxplot tool:

  1. Set “read_counts” to #: read-counts.qza

  2. Press the Execute button.

Once completed, for the new entry in your history, use the Edit button to set the name as follows:

(Renaming is optional, but it will make any subsequent steps easier to complete.)

History Name

“Name” to set (be sure to press Save)

#: qiime2 ps-plot readCountsBoxplot [...] : visualization.qzv

RCBoxplot.qzv

Ps-plot enrichmentRCBoxplot

Here we will test q2-ps-plot’s enrichmentRCBoxplot module by running the following command:

enrichedBoxplot_viz, = ps_plot_actions.enrichmentRCBoxplot(
    enriched_dir=enrich,
)

action_results <- ps_plot_actions$enrichmentRCBoxplot(
    enriched_dir=enrich,
)
enrichedBoxplot_viz <- action_results$visualization

qiime ps-plot enrichmentRCBoxplot \
  --i-enriched-dir autopepsirf-diffEnrich/enrich.qza \
  --o-visualization enrichedBoxplot.qzv

zScatter, = use.action(
 use.UsageAction(plugin_id='ps_plot', action_id='enrichmentRCBoxplot'),
 use.UsageInputs(
     enriched_dir = enriched
 ),
 use.UsageOutputNames(
     visualization = "enrichedBoxplot"
 )
 )
Using the qiime2 ps-plot enrichmentRCBoxplot tool:

  1. Set “enriched_dir” to #: enrich.qza

  2. Press the Execute button.

Once completed, for the new entry in your history, use the Edit button to set the name as follows:

(Renaming is optional, but it will make any subsequent steps easier to complete.)

History Name

“Name” to set (be sure to press Save)

#: qiime2 ps-plot enrichmentRCBoxplot [...] : visualization.qzv

enrichedBoxplot.qzv

Ps-plot repScatters

Here we will test q2-ps-plot’s repScatters module by running the following command:

ZRepScatter_viz, = ps_plot_actions.repScatters(
    zscore=zscore,
    source=samples_col_mdc,
)

action_results <- ps_plot_actions$repScatters(
    zscore=zscore,
    source=samples_col_mdc,
)
ZRepScatter_viz <- action_results$visualization

qiime ps-plot repScatters \
  --i-zscore autopepsirf-diffEnrich/zscore.qza \
  --m-source-file samples-source.tsv \
  --m-source-column source \
  --o-visualization ZRepScatter.qzv

zScatter, = use.action(
 use.UsageAction(plugin_id='ps_plot', action_id='repScatters'),
 use.UsageInputs(
     zscore = zscore,
     source = samples_col,
 ),
 use.UsageOutputNames(
     visualization = "ZRepScatter"
 )
 )
Using the qiime2 ps-plot repScatters tool:

  1. Expand the additional options section

    1. Set “zscore” to #: zscore.qza

    2. For “source”:

      1. Leave as Metadata from TSV

      2. Set “Metadata Source” to samples-source.tsv

      3. Set “Column Name” to source

  2. Press the Execute button.

Once completed, for the new entry in your history, use the Edit button to set the name as follows:

(Renaming is optional, but it will make any subsequent steps easier to complete.)

History Name

“Name” to set (be sure to press Save)

#: qiime2 ps-plot repScatters [...] : visualization.qzv

ZRepScatter.qzv

Ps-plot zenrich

Here we will test q2-ps-plot’s zenrich module by running the following command (replace pepsirf_binary with how you call pepsirf on your machine):

zenrich_scatter_viz, = ps_plot_actions.zenrich(
    data=IM0032_pA_PV1_subset_CS,
    zscores=zscore,
    source=samples_col_mdc,
    negative_controls=['SB_pA_A', 'SB_pA_B', 'SB_pA_D'],
    pepsirf_binary='/home/runner/work/pepsirf-q2-plugin-docs/pepsirf-q2-plugin-docs/pepsirf',
)

action_results <- ps_plot_actions$zenrich(
    data=IM0032_pA_PV1_subset_CS,
    zscores=zscore,
    source=samples_col_mdc,
    negative_controls=list('SB_pA_A', 'SB_pA_B', 'SB_pA_D'),
    pepsirf_binary='/home/runner/work/pepsirf-q2-plugin-docs/pepsirf-q2-plugin-docs/pepsirf',
)
zenrich_scatter_viz <- action_results$visualization

qiime ps-plot zenrich \
  --i-data IM0032-pA-PV1-subset-CS.qza \
  --i-zscores autopepsirf-diffEnrich/zscore.qza \
  --m-source-file samples-source.tsv \
  --m-source-column source \
  --p-negative-controls SB_pA_A SB_pA_B SB_pA_D \
  --p-pepsirf-binary /home/runner/work/pepsirf-q2-plugin-docs/pepsirf-q2-plugin-docs/pepsirf \
  --o-visualization zenrich-scatter.qzv

zenrichScat, = use.action(
 use.UsageAction(plugin_id='ps_plot', action_id='zenrich'),
 use.UsageInputs(
     data = col_sum,
     zscores = zscore,
     source = samples_col,
     negative_controls = ["SB_pA_A","SB_pA_B","SB_pA_D"],
     pepsirf_binary = "/home/runner/work/pepsirf-q2-plugin-docs/pepsirf-q2-plugin-docs/pepsirf"
 ),
 use.UsageOutputNames(
     visualization = "zenrich_scatter"
 )
 )
Using the qiime2 ps-plot zenrich tool:

  1. Set “data” to #: IM0032-pA-PV1-subset-CS.qza

  2. Set “zscores” to #: zscore.qza

  3. Expand the additional options section

    1. For “negative_controls”, use the + negative_controls button to add the corresponding values:

      1. Add “element” set to SB_pA_A

      2. Add “element” set to SB_pA_B

      3. Add “element” set to SB_pA_D

    2. For “source”:

      1. Leave as Metadata from TSV

      2. Set “Metadata Source” to samples-source.tsv

      3. Set “Column Name” to source

    3. Set “pepsirf_binary” to /home/runner/work/pepsirf-q2-plugin-docs/pepsirf-q2-plugin-docs/pepsirf

  4. Press the Execute button.

Once completed, for the new entry in your history, use the Edit button to set the name as follows:

(Renaming is optional, but it will make any subsequent steps easier to complete.)

History Name

“Name” to set (be sure to press Save)

#: qiime2 ps-plot zenrich [...] : visualization.qzv

zenrich-scatter.qzv