Transcriptomic Analysis
Running RNA-seq analyses pipelines in KBase
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Running RNA-seq analyses pipelines in KBase
Last updated
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KBase offers a powerful suite of . Starting with short reads, you can use the tool suite to assemble, quantify long transcripts, and identify differentially expressed genes. You can also compare the expression data with the flux when studying metabolic models in KBase and identify pathways where expression and flux agree or conflict.
The RNA-seq pipeline in KBase is modular and consists of three steps. You can pick any of the multiple Apps available for a given step depending on your preference or individual characteristics of the App.
Read Alignment: to map short reads to the reference genome. The output is a set of BAM alignments and Qualimap report. You can download the alignment output object generated by aligner Apps for further analysis.
Transcriptome Assembly and Quantification: to generate full-length transcripts and quantify transcripts and genes as appropriate. You can view downloadable normalized full expression matrices in FPKM (fragments per kilobase of exon model per million mapped reads) and TPM (transcripts per million).
Differential Gene Expression: Generate gene- or transcript-level based on the quantification. Run after selecting appropriate q-value and fold change cutoffs as input parameters for the filtering of the differential gene expression.
Filtering: You can based on fold-change or adjusted p-value. You can also based on LOR or ANOVA.
Clustering: Depending on preference, run the , or clustering App to group features into clusters based on gene expression. You can also visualize the clusters as an interactive heatmap.
Functional Enrichment: in plant genomes for a set of features using associated GO terms.
Integration into Metabolic Models: Assimilate the expression data from RNA-seq into the metabolic models to and thus identify pathways where expression and flux agree or conflict.
– bacterium-based example of an RNAseq workflow using a HISAT2/StringTie/DESeq2 pipeline
– plant-based example of an RNAseq workflow using a HISAT2/StringTie/DESeq2 pipeline
– plant-based example of using KBase to integrate full genome RNA-seq analysis and a metabolic model to generate a reaction matrix
Kumari et al. (2021) A KBase case study on genome-wide transcriptomics and plant primary metabolism in response to drought stress in Sorghum. Current Plant Biology 28.