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Training Data for "Metatranscriptomics analysis using microbiome RNASeq data"

Bérénice Batut; Subina Mehta; Praveen Kumar; Pratik Jagtap

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<oai_dc:dc xmlns:dc="" xmlns:oai_dc="" xmlns:xsi="" xsi:schemaLocation="">
  <dc:creator>Bérénice Batut</dc:creator>
  <dc:creator>Subina Mehta</dc:creator>
  <dc:creator>Praveen Kumar</dc:creator>
  <dc:creator>Pratik Jagtap</dc:creator>
  <dc:description>Microbiomes play a critical role in host health, disease, and the environment.. Functional microbiome analysis which estimates the functional groups expressed by microbial community enables researchers to look beyond taxonomic composition and correlation with the condition under study. Using microbial community RNA-Seq data and subsequent metatranscriptomics workflows to elucidate the functional complement of the microbiome is gaining interest in the field.
This tutorial from Galaxy training network will introduce researchers to the basic concepts of metatranscriptomics data analysis. It takes in paired-end datasets of raw shotgun sequences (in FastQ format) as an input and:

	extract and analyze the community structure (taxonomic information)
	extract and analyze the community functions (functional information)
	combine taxonomic and functional information to offer insights into taxonomic contribution to a function or functions expressed by a particular taxonomy.

The dataset used in the tutorial comes from a time-serie analysis of a microbial community inside a bioreactor (Kunath et al, ISME, 2018). Only the data for one time point (1st) and a biological replicate (A) is analyzed here, after having been trimmed out the original file for the purpose of saving time and resources.</dc:description>
  <dc:title>Training Data for "Metatranscriptomics analysis using microbiome RNASeq data"</dc:title>
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