MicrobiomeStat Tutorial
  • Track, Analyze, Visualize: Unravel Your Microbiome's Temporal Pattern with MicrobiomeStat.
  • INTRODUCTION
    • Exploring MicrobiomeStat: A Consideration for Your Research Toolkit
  • Setting Up MicrobiomeStat: Installation and Data Preparation
    • Installation Guide
    • Creating the MicrobiomeStat Data Object
      • Building MicrobiomeStat from Matrix and Data.frame
      • Converting Data from Phyloseq into MicrobiomeStat
      • Importing Data from QIIME2 into MicrobiomeStat
      • Importing Data from BIOM into MicrobiomeStat
      • Converting SummarizedExperiment into MicrobiomeStat
      • Converting DGEList Data into MicrobiomeStat
      • Converting DESeqDataSet into MicrobiomeStat
      • Importing Data from DADA2 into MicrobiomeStat
      • Importing Data from Mothur into MicrobiomeStat
  • Single-Point Analysis
    • Introduction
    • Alpha Diversity Analysis
    • Beta Diversity Analysis
    • Feature-level Analysis
    • One-Click Reports Generation
  • Paired Samples Analysis
    • Introduction
    • Alpha Diversity Analysis
    • Beta Diversity Analysis
    • Feature-level Analysis
    • One-Click Reports Generation
  • Longitudinal Analysis
    • Introduction
    • Alpha Diversity Analysis
    • Beta Diversity Analysis
    • Feature-level Analysis
    • One-Click Reports Generation
  • Data Manipulation and Transformation
    • Data Summary
    • Data Aggregation
    • Data Normalization
    • Data Filtering
    • Data Validation
    • Data Combination
    • Metadata Management
    • Color Palette
  • Frequently Asked Questions (FAQ)
    • General FAQs
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  • Code to Import Data

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  1. Setting Up MicrobiomeStat: Installation and Data Preparation
  2. Creating the MicrobiomeStat Data Object

Importing Data from DADA2 into MicrobiomeStat

Learn the steps to import data from DADA2 into MicrobiomeStat's data structure.

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Last updated 1 year ago

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This guide will walk you through the steps required to import data from DADA2 into MicrobiomeStat.

Download Necessary Files

Code to Import Data

# This function requires the `Biostrings` and `yaml` packages.
 
# If you encounter issues when running the example code, please ensure that you have installed and loaded these packages.
library(Biostrings)
library(yaml)
# Read the sequence table from the downloaded RDS file
seq_tab <- readRDS("path_to_your_downloaded_folder/dada2_seqtab.rds")

# Read the taxonomy table from the downloaded RDS file
tax_tab <- readRDS("path_to_your_downloaded_folder/dada2_taxtab.rds")

# Read the sample metadata from the downloaded txt file
sam_tab <- read.table(
  "path_to_your_downloaded_folder/dada2_samdata.txt",
  sep = "\t",
  header = TRUE,
  row.names = 1
)

# Convert DADA2 data into a MicrobiomeStat data object
data_obj <- mStat_import_dada2_as_data_obj(
  seq_tab = seq_tab,
  tax_tab = tax_tab,
  sam_tab = sam_tab
)

Note: Ensure to replace "path_to_your_downloaded_folder" with the actual path where you've saved the downloaded files.

11KB
dada2_seqtab.rds
Sequence table (seq_tab) - This table from DADA2 contains sample-specific sequence abundance data. Rows represent samples, and columns correspond to sequences.
9KB
dada2_taxtab.rds
Taxonomy assignment table (tax_tab) - This table provides taxonomic classifications for sequences, helping users understand the biological context of the identified sequences.
397B
dada2_samdata.txt
Sample metadata table (`sam_tab`) - This table offers detailed metadata for each sample, enriching the context and facilitating more in-depth analyses.
Structure of the MicrobiomeStat data object after importing DADA2 data. This visualization highlights the different components of the data object, including the feature table, taxonomy table, and sample metadata, facilitating a comprehensive understanding of the imported dataset.