Taxonomic Profiling

Published

Jun 2026

ID: MICROB-007
Type: System Component
Audience: Students, researchers, analysts, and practitioners
Theme: Connecting microbiome features to microbial identities

Introduction

Taxonomic profiling is the stage where microbiome features are connected to microbial identities and summarized across samples.

After feature generation, the analysis contains a feature table. However, a feature identifier such as ASV_001 is not biologically meaningful on its own. Taxonomic profiling adds interpretation by linking features to microbial groups such as phylum, family, genus, or species.

This chapter uses the example feature table created in Chapter 06 to demonstrate a lightweight taxonomic profiling workflow.

The example data are toy data for workflow testing and should not be used for biological interpretation.

Why Taxonomic Profiling Matters

Taxonomic profiling helps answer the question:

Which microbes are present, and how abundant are they across samples?

Taxonomic profiles support:

community composition summaries
dominant taxon identification
group-level microbial comparisons
relative abundance visualization
downstream biological interpretation
report-ready microbiome summaries

Taxonomic profiling is often one of the first outputs stakeholders expect from microbiome analysis.

Position in the Microbiome Analysis System

Taxonomic profiling occurs after feature generation and before diversity analysis, functional profiling, differential analysis, and biological interpretation.

Show code

flowchart LR
  A[Feature Generation] --> B[Taxonomic Profiling]
  B --> C[Diversity Analysis]
  B --> D[Differential Analysis]
  B --> E[Biological Interpretation]

flowchart LR
  A[Feature Generation] --> B[Taxonomic Profiling]
  B --> C[Diversity Analysis]
  B --> D[Differential Analysis]
  B --> E[Biological Interpretation]

At this stage, features are summarized into microbial taxonomic groups.

From Features to Taxa

A feature table may look like this:

feature_id    SRR17868090    SRR17868091    SRR17868092
ASV_001       120            85             40
ASV_002       15             30             75

Feature metadata may provide taxonomy:

feature_id    taxonomy
ASV_001       Bacteria; Firmicutes; ...; Lactobacillus
ASV_002       Bacteria; Bacteroidota; ...; Bacteroides

Taxonomic profiling joins these two files and summarizes abundance by taxonomic rank.

Taxonomic Ranks

Common taxonomic ranks include:

kingdom
phylum
class
order
family
genus
species

Marker-gene datasets often provide confident assignments at higher ranks, while species-level assignment may be less reliable depending on the target region, reference database, and classifier.

Shotgun metagenomic datasets may provide species- or strain-level information depending on method and database.

Relative Abundance

Raw feature counts are useful, but many taxonomic summaries are shown as relative abundance.

Relative abundance is calculated within each sample:

relative abundance = taxon count / total sample count

This makes samples easier to compare visually when sequencing depth differs.

However, relative abundance is compositional. An increase in one taxon can change the apparent proportion of others, even if their absolute abundance did not change. This should be considered during interpretation.

Example Taxonomic Profiling Scripts

The following scripts provide a lightweight MAS-side taxonomic profiling example.

The workflow uses two scripts:

scripts/bash/07a-build-taxonomic-profile.sh
scripts/R/07b-plot-taxonomic-profile.R

The first script joins the example feature table with feature metadata, extracts genus-level labels, and summarizes counts and relative abundance.

The second script creates simple taxonomic profile plots using ggplot2.

07a: Build a Taxonomic Profile

Save this script as:

scripts/bash/07a-build-taxonomic-profile.sh

#!/bin/bash

###############################################################################
# Microbiome Analysis System
# 07a-build-taxonomic-profile.sh
#
# Purpose:
#   Build a simple genus-level taxonomic profile from the example feature table.
#
# Inputs:
#   data/features/feature-table.tsv
#   data/features/feature-metadata.tsv
#
# Outputs:
#   data/taxonomy/feature-taxonomy-long.tsv
#   data/taxonomy/genus-counts-long.tsv
#   data/taxonomy/genus-relative-abundance.tsv
#
# Usage:
#   bash scripts/bash/07a-build-taxonomic-profile.sh
###############################################################################

set -e

FEATURE_DIR="data/features"
TAXONOMY_DIR="data/taxonomy"
REPORT_DIR="data/reports"

FEATURE_TABLE="${FEATURE_DIR}/feature-table.tsv"
FEATURE_METADATA="${FEATURE_DIR}/feature-metadata.tsv"

LONG_FEATURE_TAXONOMY="${TAXONOMY_DIR}/feature-taxonomy-long.tsv"
GENUS_COUNTS="${TAXONOMY_DIR}/genus-counts-long.tsv"
GENUS_REL_ABUND="${TAXONOMY_DIR}/genus-relative-abundance.tsv"
REPORT_FILE="${REPORT_DIR}/taxonomic-profile-report.tsv"

mkdir -p "${TAXONOMY_DIR}"
mkdir -p "${REPORT_DIR}"

if [ ! -s "${FEATURE_TABLE}" ]; then
  echo "Missing feature table: ${FEATURE_TABLE}"
  echo "Run: bash scripts/bash/06a-create-example-feature-table.sh"
  exit 1
fi

if [ ! -s "${FEATURE_METADATA}" ]; then
  echo "Missing feature metadata: ${FEATURE_METADATA}"
  echo "Run: bash scripts/bash/06a-create-example-feature-table.sh"
  exit 1
fi

echo "Building genus-level taxonomic profile..."

awk -F '\t' '
NR == FNR {
  if (FNR > 1) {
    taxonomy=$3;
    n=split(taxonomy, parts, ";");
    genus=parts[n];
    gsub(/^ +| +$/, "", genus);
    if (genus == "" || genus == "NA") genus="Unclassified";
    tax[$1]=taxonomy;
    genus_map[$1]=genus;
  }
  next;
}
FNR == 1 {
  for (i=2; i<=NF; i++) {
    sample[i]=$i;
  }
  print "feature_id\tsample_id\tcount\ttaxonomy\tgenus";
  next;
}
{
  feature=$1;
  for (i=2; i<=NF; i++) {
    print feature "\t" sample[i] "\t" $i "\t" tax[feature] "\t" genus_map[feature];
  }
}
' "${FEATURE_METADATA}" "${FEATURE_TABLE}" > "${LONG_FEATURE_TAXONOMY}"

awk -F '\t' '
BEGIN {OFS="\t"}
NR == 1 {next}
{
  key=$2 "\t" $5;
  counts[key]+=$3;
}
END {
  print "sample_id", "genus", "count";
  for (key in counts) {
    print key, counts[key];
  }
}
' "${LONG_FEATURE_TAXONOMY}" | sort -k1,1 -k2,2 > "${GENUS_COUNTS}"

awk -F '\t' '
BEGIN {OFS="\t"}
NR == 1 {next}
{
  total[$1]+=$3;
  count[$1 "\t" $2]+=$3;
}
END {
  print "sample_id", "genus", "count", "relative_abundance";
  for (key in count) {
    split(key, parts, "\t");
    sample=parts[1];
    genus=parts[2];
    rel=0;
    if (total[sample] > 0) rel=count[key]/total[sample];
    print sample, genus, count[key], rel;
  }
}
' "${GENUS_COUNTS}" | sort -k1,1 -k2,2 > "${GENUS_REL_ABUND}"

feature_count=$(tail -n +2 "${FEATURE_TABLE}" | wc -l | tr -d ' ')
sample_count=$(head -n 1 "${FEATURE_TABLE}" | awk -F '\t' '{print NF-1}')
genus_count=$(tail -n +2 "${GENUS_COUNTS}" | awk -F '\t' '{print $2}' | sort -u | wc -l | tr -d ' ')

printf "metric\tvalue\n" > "${REPORT_FILE}"
printf "feature_count\t%s\n" "${feature_count}" >> "${REPORT_FILE}"
printf "sample_count\t%s\n" "${sample_count}" >> "${REPORT_FILE}"
printf "genus_count\t%s\n" "${genus_count}" >> "${REPORT_FILE}"
printf "taxonomic_rank\tgenus\n" >> "${REPORT_FILE}"
printf "profile_status\tREADY_FOR_PLOTTING\n" >> "${REPORT_FILE}"

echo "Created:"
echo "  ${LONG_FEATURE_TAXONOMY}"
echo "  ${GENUS_COUNTS}"
echo "  ${GENUS_REL_ABUND}"
echo "  ${REPORT_FILE}"

Run it from the MAS project root:

bash scripts/bash/07a-build-taxonomic-profile.sh

This creates:

data/taxonomy/feature-taxonomy-long.tsv
data/taxonomy/genus-counts-long.tsv
data/taxonomy/genus-relative-abundance.tsv
data/reports/taxonomic-profile-report.tsv

07b: Plot the Taxonomic Profile

Save this script as:

scripts/R/07b-plot-taxonomic-profile.R

###############################################################################
# Microbiome Analysis System
# 07b-plot-taxonomic-profile.R
#
# Purpose:
#   Plot a simple genus-level relative abundance profile.
#
# Usage:
#   Rscript scripts/R/07b-plot-taxonomic-profile.R
###############################################################################

library(readr)
library(dplyr)
library(ggplot2)
library(stringr)

taxonomy_dir <- "data/taxonomy"
figure_dir <- "figures"
table_dir <- "tables"

dir.create(figure_dir, recursive = TRUE, showWarnings = FALSE)
dir.create(table_dir, recursive = TRUE, showWarnings = FALSE)

rel_abund_file <- file.path(taxonomy_dir, "genus-relative-abundance.tsv")

if (!file.exists(rel_abund_file)) {
  stop(
    "Missing genus relative abundance file: ",
    rel_abund_file,
    "\nRun: bash scripts/bash/07a-build-taxonomic-profile.sh"
  )
}

taxa <- read_tsv(rel_abund_file, show_col_types = FALSE)

taxa_plot <- taxa %>%
  mutate(
    relative_abundance_percent = relative_abundance * 100,
    genus = str_replace_all(genus, "_", " ")
  )

write_tsv(
  taxa_plot,
  file.path(table_dir, "genus-relative-abundance-for-plot.tsv")
)

p <- ggplot(
  taxa_plot,
  aes(
    x = sample_id,
    y = relative_abundance_percent,
    fill = genus
  )
) +
  geom_col() +
  labs(
    title = "Example Genus-Level Taxonomic Profile",
    subtitle = "Toy MAS example data for workflow testing",
    x = "Sample",
    y = "Relative abundance (%)",
    fill = "Genus"
  ) +
  theme_minimal(base_size = 12) +
  theme(
    axis.text.x = element_text(angle = 45, hjust = 1)
  )

ggsave(
  filename = file.path(figure_dir, "genus-relative-abundance-profile.png"),
  plot = p,
  width = 8,
  height = 5,
  dpi = 300
)

message("Created:")
message("  ", file.path(table_dir, "genus-relative-abundance-for-plot.tsv"))
message("  ", file.path(figure_dir, "genus-relative-abundance-profile.png"))

Run it from the MAS project root:

Rscript scripts/R/07b-plot-taxonomic-profile.R

This creates:

tables/genus-relative-abundance-for-plot.tsv
figures/genus-relative-abundance-profile.png

Running the Complete Taxonomic Profiling Example

If you are continuing from Chapter 06, first make sure the example feature table exists:

bash scripts/bash/06a-create-example-feature-table.sh
bash scripts/bash/06b-check-feature-table.sh

Then build and plot the taxonomic profile:

bash scripts/bash/07a-build-taxonomic-profile.sh
Rscript scripts/R/07b-plot-taxonomic-profile.R
cat data/reports/taxonomic-profile-report.tsv

This produces genus-level count and relative abundance tables, plus a simple stacked bar plot.

Example Genus Relative Abundance Table

The generated table may look like this:

sample_id   genus   count   relative_abundance
SRR17868090 Akkermansia 5   0.027027
SRR17868090 Bacteroides 15  0.081081
SRR17868090 Bifidobacterium 0   0
SRR17868090 Escherichia-Shigella    45  0.243243
SRR17868090 Lactobacillus   120 0.648649

Relative abundance values should be interpreted as proportions within each sample.

Interpreting Taxonomic Profiles

Taxonomic profiles provide a biological overview of microbial community composition.

They can help identify:

dominant taxa
rare taxa
sample-level patterns
possible group differences
taxa that may require closer investigation

However, a taxonomic profile is usually descriptive. It should not be overinterpreted as evidence of disease, function, causality, or mechanism without additional analysis and biological context.

Common Taxonomic Profiling Issues

Common issues include:

incomplete taxonomic assignments
inconsistent rank names
ambiguous genus or species labels
database-dependent classifications
low-confidence assignments
different naming conventions across tools
overinterpretation of species-level labels
compositional effects in relative abundance data

These issues should be documented during reporting.

Taxonomic Profiling Outputs

At the end of this stage, MAS should have:

feature-taxonomy long table
taxon-level count table
taxon-level relative abundance table
taxonomic profile report
taxonomic profile plot
notes on taxonomy source and limitations

Show code

flowchart LR
  A[Feature Table] --> B[Feature Metadata]
  B --> C[Taxonomic Profile]
  C --> D[Relative Abundance Table]
  D --> E[Taxonomic Plot]
  E --> F[Biological Interpretation]

flowchart LR
  A[Feature Table] --> B[Feature Metadata]
  B --> C[Taxonomic Profile]
  C --> D[Relative Abundance Table]
  D --> E[Taxonomic Plot]
  E --> F[Biological Interpretation]

Key Takeaways

Taxonomic profiling connects microbiome features to microbial identities.

A strong taxonomic profiling stage ensures that:

feature identifiers are linked to taxonomy
abundance is summarized at meaningful ranks
relative abundance tables are generated carefully
plots are descriptive and not overinterpreted
taxonomy source and limitations are documented

Taxonomic profiling provides one of the first interpretable views of the microbial community.

What Comes Next

The next chapter examines Diversity Analysis, where microbial communities are compared within and between samples.

# Taxonomic Profiling :::cdi-message - **ID:** MICROB-007 - **Type:** System Component - **Audience:** Students, researchers, analysts, and practitioners - **Theme:** Connecting microbiome features to microbial identities ::: ## Introduction Taxonomic profiling is the stage where microbiome features are connected to microbial identities and summarized across samples. After feature generation, the analysis contains a feature table. However, a feature identifier such as `ASV_001` is not biologically meaningful on its own. Taxonomic profiling adds interpretation by linking features to microbial groups such as phylum, family, genus, or species. This chapter uses the example feature table created in Chapter 06 to demonstrate a lightweight taxonomic profiling workflow. The example data are toy data for workflow testing and should not be used for biological interpretation. ## Why Taxonomic Profiling Matters Taxonomic profiling helps answer the question: ```text Which microbes are present, and how abundant are they across samples? ``` Taxonomic profiles support: - community composition summaries - dominant taxon identification - group-level microbial comparisons - relative abundance visualization - downstream biological interpretation - report-ready microbiome summaries Taxonomic profiling is often one of the first outputs stakeholders expect from microbiome analysis. ## Position in the Microbiome Analysis System Taxonomic profiling occurs after feature generation and before diversity analysis, functional profiling, differential analysis, and biological interpretation. ```{mermaid} flowchart LR A[Feature Generation] --> B[Taxonomic Profiling] B --> C[Diversity Analysis] B --> D[Differential Analysis] B --> E[Biological Interpretation] ``` At this stage, features are summarized into microbial taxonomic groups. ## From Features to Taxa A feature table may look like this: ```text feature_id SRR17868090 SRR17868091 SRR17868092 ASV_001 120 85 40 ASV_002 15 30 75 ``` Feature metadata may provide taxonomy: ```text feature_id taxonomy ASV_001 Bacteria; Firmicutes; ...; Lactobacillus ASV_002 Bacteria; Bacteroidota; ...; Bacteroides ``` Taxonomic profiling joins these two files and summarizes abundance by taxonomic rank. ## Taxonomic Ranks Common taxonomic ranks include: - kingdom - phylum - class - order - family - genus - species Marker-gene datasets often provide confident assignments at higher ranks, while species-level assignment may be less reliable depending on the target region, reference database, and classifier. Shotgun metagenomic datasets may provide species- or strain-level information depending on method and database. ## Relative Abundance Raw feature counts are useful, but many taxonomic summaries are shown as relative abundance. Relative abundance is calculated within each sample: ```text relative abundance = taxon count / total sample count ``` This makes samples easier to compare visually when sequencing depth differs. However, relative abundance is compositional. An increase in one taxon can change the apparent proportion of others, even if their absolute abundance did not change. This should be considered during interpretation. ## Example Taxonomic Profiling Scripts The following scripts provide a lightweight MAS-side taxonomic profiling example. The workflow uses two scripts: ```text scripts/bash/07a-build-taxonomic-profile.sh scripts/R/07b-plot-taxonomic-profile.R ``` The first script joins the example feature table with feature metadata, extracts genus-level labels, and summarizes counts and relative abundance. The second script creates simple taxonomic profile plots using `ggplot2`. ## 07a: Build a Taxonomic Profile Save this script as: ```bash scripts/bash/07a-build-taxonomic-profile.sh ``` ```bash #!/bin/bash ############################################################################### # Microbiome Analysis System # 07a-build-taxonomic-profile.sh # # Purpose: # Build a simple genus-level taxonomic profile from the example feature table. # # Inputs: # data/features/feature-table.tsv # data/features/feature-metadata.tsv # # Outputs: # data/taxonomy/feature-taxonomy-long.tsv # data/taxonomy/genus-counts-long.tsv # data/taxonomy/genus-relative-abundance.tsv # # Usage: # bash scripts/bash/07a-build-taxonomic-profile.sh ############################################################################### set -e FEATURE_DIR="data/features" TAXONOMY_DIR="data/taxonomy" REPORT_DIR="data/reports" FEATURE_TABLE="${FEATURE_DIR}/feature-table.tsv" FEATURE_METADATA="${FEATURE_DIR}/feature-metadata.tsv" LONG_FEATURE_TAXONOMY="${TAXONOMY_DIR}/feature-taxonomy-long.tsv" GENUS_COUNTS="${TAXONOMY_DIR}/genus-counts-long.tsv" GENUS_REL_ABUND="${TAXONOMY_DIR}/genus-relative-abundance.tsv" REPORT_FILE="${REPORT_DIR}/taxonomic-profile-report.tsv" mkdir -p "${TAXONOMY_DIR}" mkdir -p "${REPORT_DIR}" if [ ! -s "${FEATURE_TABLE}" ]; then echo "Missing feature table: ${FEATURE_TABLE}" echo "Run: bash scripts/bash/06a-create-example-feature-table.sh" exit 1 fi if [ ! -s "${FEATURE_METADATA}" ]; then echo "Missing feature metadata: ${FEATURE_METADATA}" echo "Run: bash scripts/bash/06a-create-example-feature-table.sh" exit 1 fi echo "Building genus-level taxonomic profile..." awk -F '\t' ' NR == FNR { if (FNR > 1) { taxonomy=$3; n=split(taxonomy, parts, ";"); genus=parts[n]; gsub(/^ +| +$/, "", genus); if (genus == "" || genus == "NA") genus="Unclassified"; tax[$1]=taxonomy; genus_map[$1]=genus; } next; } FNR == 1 { for (i=2; i<=NF; i++) { sample[i]=$i; } print "feature_id\tsample_id\tcount\ttaxonomy\tgenus"; next; } { feature=$1; for (i=2; i<=NF; i++) { print feature "\t" sample[i] "\t" $i "\t" tax[feature] "\t" genus_map[feature]; } } ' "${FEATURE_METADATA}" "${FEATURE_TABLE}" > "${LONG_FEATURE_TAXONOMY}" awk -F '\t' ' BEGIN {OFS="\t"} NR == 1 {next} { key=$2 "\t" $5; counts[key]+=$3; } END { print "sample_id", "genus", "count"; for (key in counts) { print key, counts[key]; } } ' "${LONG_FEATURE_TAXONOMY}" | sort -k1,1 -k2,2 > "${GENUS_COUNTS}" awk -F '\t' ' BEGIN {OFS="\t"} NR == 1 {next} { total[$1]+=$3; count[$1 "\t" $2]+=$3; } END { print "sample_id", "genus", "count", "relative_abundance"; for (key in count) { split(key, parts, "\t"); sample=parts[1]; genus=parts[2]; rel=0; if (total[sample] > 0) rel=count[key]/total[sample]; print sample, genus, count[key], rel; } } ' "${GENUS_COUNTS}" | sort -k1,1 -k2,2 > "${GENUS_REL_ABUND}" feature_count=$(tail -n +2 "${FEATURE_TABLE}" | wc -l | tr -d ' ') sample_count=$(head -n 1 "${FEATURE_TABLE}" | awk -F '\t' '{print NF-1}') genus_count=$(tail -n +2 "${GENUS_COUNTS}" | awk -F '\t' '{print $2}' | sort -u | wc -l | tr -d ' ') printf "metric\tvalue\n" > "${REPORT_FILE}" printf "feature_count\t%s\n" "${feature_count}" >> "${REPORT_FILE}" printf "sample_count\t%s\n" "${sample_count}" >> "${REPORT_FILE}" printf "genus_count\t%s\n" "${genus_count}" >> "${REPORT_FILE}" printf "taxonomic_rank\tgenus\n" >> "${REPORT_FILE}" printf "profile_status\tREADY_FOR_PLOTTING\n" >> "${REPORT_FILE}" echo "Created:" echo " ${LONG_FEATURE_TAXONOMY}" echo " ${GENUS_COUNTS}" echo " ${GENUS_REL_ABUND}" echo " ${REPORT_FILE}" ``` Run it from the MAS project root: ```bash bash scripts/bash/07a-build-taxonomic-profile.sh ``` This creates: ```text data/taxonomy/feature-taxonomy-long.tsv data/taxonomy/genus-counts-long.tsv data/taxonomy/genus-relative-abundance.tsv data/reports/taxonomic-profile-report.tsv ``` ## 07b: Plot the Taxonomic Profile Save this script as: ```text scripts/R/07b-plot-taxonomic-profile.R ``` ```r ############################################################################### # Microbiome Analysis System # 07b-plot-taxonomic-profile.R # # Purpose: # Plot a simple genus-level relative abundance profile. # # Usage: # Rscript scripts/R/07b-plot-taxonomic-profile.R ############################################################################### library(readr) library(dplyr) library(ggplot2) library(stringr) taxonomy_dir <- "data/taxonomy" figure_dir <- "figures" table_dir <- "tables" dir.create(figure_dir, recursive = TRUE, showWarnings = FALSE) dir.create(table_dir, recursive = TRUE, showWarnings = FALSE) rel_abund_file <- file.path(taxonomy_dir, "genus-relative-abundance.tsv") if (!file.exists(rel_abund_file)) { stop( "Missing genus relative abundance file: ", rel_abund_file, "\nRun: bash scripts/bash/07a-build-taxonomic-profile.sh" ) } taxa <- read_tsv(rel_abund_file, show_col_types = FALSE) taxa_plot <- taxa %>% mutate( relative_abundance_percent = relative_abundance * 100, genus = str_replace_all(genus, "_", " ") ) write_tsv( taxa_plot, file.path(table_dir, "genus-relative-abundance-for-plot.tsv") ) p <- ggplot( taxa_plot, aes( x = sample_id, y = relative_abundance_percent, fill = genus ) ) + geom_col() + labs( title = "Example Genus-Level Taxonomic Profile", subtitle = "Toy MAS example data for workflow testing", x = "Sample", y = "Relative abundance (%)", fill = "Genus" ) + theme_minimal(base_size = 12) + theme( axis.text.x = element_text(angle = 45, hjust = 1) ) ggsave( filename = file.path(figure_dir, "genus-relative-abundance-profile.png"), plot = p, width = 8, height = 5, dpi = 300 ) message("Created:") message(" ", file.path(table_dir, "genus-relative-abundance-for-plot.tsv")) message(" ", file.path(figure_dir, "genus-relative-abundance-profile.png")) ``` Run it from the MAS project root: ```bash Rscript scripts/R/07b-plot-taxonomic-profile.R ``` This creates: ```text tables/genus-relative-abundance-for-plot.tsv figures/genus-relative-abundance-profile.png ``` ## Running the Complete Taxonomic Profiling Example If you are continuing from Chapter 06, first make sure the example feature table exists: ```bash bash scripts/bash/06a-create-example-feature-table.sh bash scripts/bash/06b-check-feature-table.sh ``` Then build and plot the taxonomic profile: ```bash bash scripts/bash/07a-build-taxonomic-profile.sh Rscript scripts/R/07b-plot-taxonomic-profile.R cat data/reports/taxonomic-profile-report.tsv ``` This produces genus-level count and relative abundance tables, plus a simple stacked bar plot. ## Example Genus Relative Abundance Table The generated table may look like this: ```text sample_id genus count relative_abundance SRR17868090 Akkermansia 5 0.027027 SRR17868090 Bacteroides 15 0.081081 SRR17868090 Bifidobacterium 0 0 SRR17868090 Escherichia-Shigella 45 0.243243 SRR17868090 Lactobacillus 120 0.648649 ``` Relative abundance values should be interpreted as proportions within each sample. ## Interpreting Taxonomic Profiles Taxonomic profiles provide a biological overview of microbial community composition. They can help identify: - dominant taxa - rare taxa - sample-level patterns - possible group differences - taxa that may require closer investigation However, a taxonomic profile is usually descriptive. It should not be overinterpreted as evidence of disease, function, causality, or mechanism without additional analysis and biological context. ## Common Taxonomic Profiling Issues Common issues include: - incomplete taxonomic assignments - inconsistent rank names - ambiguous genus or species labels - database-dependent classifications - low-confidence assignments - different naming conventions across tools - overinterpretation of species-level labels - compositional effects in relative abundance data These issues should be documented during reporting. ## Taxonomic Profiling Outputs At the end of this stage, MAS should have: - feature-taxonomy long table - taxon-level count table - taxon-level relative abundance table - taxonomic profile report - taxonomic profile plot - notes on taxonomy source and limitations ```{mermaid} flowchart LR A[Feature Table] --> B[Feature Metadata] B --> C[Taxonomic Profile] C --> D[Relative Abundance Table] D --> E[Taxonomic Plot] E --> F[Biological Interpretation] ``` ## Key Takeaways Taxonomic profiling connects microbiome features to microbial identities. A strong taxonomic profiling stage ensures that: - feature identifiers are linked to taxonomy - abundance is summarized at meaningful ranks - relative abundance tables are generated carefully - plots are descriptive and not overinterpreted - taxonomy source and limitations are documented Taxonomic profiling provides one of the first interpretable views of the microbial community. ## What Comes Next The next chapter examines **Diversity Analysis**, where microbial communities are compared within and between samples.