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On this page
  • Reads Management
  • Alignment
  • Assembly
  • Differential Expression
  • Downstream Analyses

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  1. Using Apps
  2. Analysis Apps in KBase

Expression & Transcriptomics

Some of the tools in KBase available for expression analysis

PreviousChemical AbundanceNextApps in Beta

Last updated 2 years ago

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KBase offers a powerful suite of . Starting with short reads, you can use the tool suite to analyze transcriptomic data in a . 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.

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

Reads Management

  • – Read quality analysis

  • – Remove adapter sequences from reads

  • – Read trimming and removing Illumina adapters

Alignment

  • – aligns the sequencing reads for a set of two or more samples to long reference sequences of a prokaryotic genome using Bowtie2 and outputs a set of alignments for the given sample set in BAM format.

  • – aligns the sequencing reads for a set of two or more samples to an eukaryotic genome using TopHat2 in order to identify splice junctions between exons with the help of Bowtie2 mapping program.

  • – aligns the sequencing reads for a set of two or more samples to long reference sequences of a genome using HISAT2 and outputs a set of alignments for the given sample set or reads set in BAM format.

  • – aligns the sequencing reads of a single or a set of two (paired end) reads to long reference sequences of a prokaryotic genome using the STAR alignment program.

Assembly

  • – assembles transcripts for a given sample or a sample set using Cufflinks so that you can view the relative abundances of the assembled transcripts in a histogram, obtained as output from Cufflinks.

  • – assembles transcripts for a given sample or a sample set using StringTie so that you can view the relative abundances of the assembled transcripts in a histogram.

Differential Expression

Downstream Analyses

– uses the Cufflinks transcripts for two or more samples to calculate gene and transcript levels in more than one condition and finds significant changes in the expression levels.

– uses the transcripts for two or more samples obtained from either Cufflinks or StringTie to calculate gene and transcript levels in more than one condition and finds significant changes in the expression levels.

– uses the transcripts for two or more samples obtained from either Cufflinks or StringTie to calculate gene and transcript levels in more than one condition and finds significant changes in the expression levels.

– Filter an expression matrix using either Log Odds Ratio (LOR) or ANalysis of VAriance (ANOVA) algorithms.

– Perform hierarchical clustering to group gene expression data into a dendrogram.

– Generate reasonable numbers of clusters (K) for use in the App.

– Perform K-means clustering to group expression data for observing and analyzing patterns of gene expression.

– Perform weighted gene co-expression network analysis (WGCNA) to detect gene clusters and expression patterns.

– display heatmap of expressed genes.

– display multi-cluster heatmap of expressed genes.

expression analysis Apps
expression analysis tools
Assess Read Quality with FastQC
Cutadapt
Trim Reads with Trimmomatic
Align Reads using Bowtie2
Align Reads using TopHat2
Align Reads using HISAT2
Align Reads using STAR
Assemble Transcripts using Cufflinks
Assemble Transcripts using StringTie
Identify Differential Expression using Cuffdiff
Create Differential Expression Matrix using Ballgown
Create Differential Expression Matrix using DESeq2
Filter Expression Matrix
Cluster Expression Data – Hierarchical
Estimate K for K-means Clustering
Cluster Expression Data - K-Means
Cluster Expression Data – K-means
Cluster Expression Data – WGCNA
View Interactive Heatmap
View Multi-cluster Heatmap