New RNA Apps in BaseSpace

We are excited to launch the TruSeq Targeted RNA v1.0 and Small RNA v1.0 Core Apps in BaseSpace, which are some of the most feature-rich Apps we have launched to date.

 

TruSeq Targeted RNA v1.0

Small RNA v1.0

A high level overview of the Apps is provided below. More detailed information about the Apps can be found in their respective Core Apps application guides.

TruSeq Targeted RNA v1.0 App

The BaseSpace TruSeq Targeted RNA v1.0 App analyzes RNA samples prepared using TruSeq Targeted RNA Expression Kits. The Targeted RNA App aligns reads against regions specified in the manifest file, quantifies the relative expression of genes and isoforms between several samples, and compares abundance across samples. An example of the input form for running the TruSeq Targeted RNA App is shown below.

 

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One of the new features available in the TruSeq Targeted RNA App is the ability to define multiple groups for analysis. Once the groups are defined, pairwise differential expression analysis will be performed between each of the groups. If only a single group is provided then differential expression is not performed. Users can also perform gene-based normalization which normalizes the counts to a gene or set of genes within the sample. If this option is selected a semi-colon list of gene names should also be provided.

The output of the TruSeq Targeted RNA App is an interactive heat map which clusters the sample in the x-axis and the amplicons in the y-axis. An example of the heat map is shown below.

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In addition to the heat map an interactive scatter plot comparing the normalized counts for any two groups of samples is provided. The scatter plot is also associated with a table depicting the differential expression results. Both are shown below.

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Small RNA v1.0 app

The BaseSpace Small RNA v1.0 App analyzes small RNA samples. The Small RNA App supports TruSeq Small RNA Sample Preparation Kits and assumes that reads have been properly adapter-trimmed. If necessary, adapter trimming can performed using the FASTQ Toolkit v1.0 App. Adapter trimming should only be performed on the 3′ end of the read. The presence of adapters can be determined using the FastQC App. When trimming adapter, the minimum read length should be set to 20 or a reasonable length for small RNA. For the TruSeq Small RNA Sample Prep Kit the adapter sequence is 5’ TGGAATTCTCGGGTGCCAAGG.

The App aligns reads against four reference databases (abundant, mature miRNA, other RNA, and genomic) and outputs hits to mature miRNAs, isomiRs, and piRNAs. Optionally, the App performs novel precursor discovery and pairwise differential expression analysis. Pairwise differential expression analysis identifies differentially expressed miRNAs, precursor groups, miRNA families, and piRNAs for each pair of sample groups. An example of the input form for running the Small RNA App is shown below.

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The App supports analysis of human (hg19), mouse (mm10) and rat (rn5) genomes. The first option is to enable novel precursor discovery using miRDeep*. If this option is selected, novel precursor prediction is performed for each sample group and hence sample grouping affects the results. The next option is to perform pair-wise differential expression between all groups of samples using DESeq2. The sample groups can be defined in the samples section of the input form. Alternatively if all by all pair-wise differential expression analysis is not warranted a user can select the “Select Pairs of Groups for Differential Expression Analysis option” and define which groups will be used for differential expression analysis.

The output of the analysis are individual reports for each of the sample groups, an aggregate report which contains the differential expression and group results, and an individual sample report for each sample be analyzed.

In the individual sample report we provide a set of QC statistics such as the distribution of read lengths, read distribution (i.e. abundant, genome, miRNA, other RNA, or unaligned), Abundant Distribution (i.e. Mito, adapter, Human 5S, Human Ribosomal, etc.), miRNA (i.e. known mature, isoMir, etc.) and other (i.e. linc, pi, snRNA, etc).

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The individual sample report also contains a summary and top sequences for each marker type below.

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Finally the individual sample report contains a visualization by precursor section to visualize mature and isomiR hits for each precursor. In addition to providing a nice visualization of the precursor molecule the counts for each miRNA or isomirR is provided. The visualization also provides a link out to miRBase providing additional information about precursor and associated miRNA.

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The Aggregate Summary report contains information about groups of samples and the differential expression results. Like the individual sample report the aggregate report provides QC statistics but on groups of sample as show below.

 

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If “Enable Novel Precursor Discovery” is selected then a section containing Novel miRNAs predicted by miRDeep* is provided.

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Finally, if selected, a differential expression analysis section is provided.

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The differential expression analysis section is divided in miRNA families, precursor groups, miRNAs, and piRNAs. Each section contains multiple tabs as shown below.

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The first tab contains a sample correlation matrix, the second tab is a PCA plot looking at the projection of the all the sample on the first and second principle components, the third tab is a heat map that is similar to the heat map show above for the TruSeq Targeted RNA App and finally a pairwise analysis tab which contains an MA plot and an interactive differential expression table as shown below.

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Other Apps

We are also excited to publish a new 3rd party small RNA App called miRNAs Analysis from B&GU at the University of Torino.

miRNAs Analysis

This App allows the detection of differentially expressed miRNAs between two conditions and performs the following steps:

  • trims adapters using cutadapt
  • maps trimmed reads on miRNA precursors using SHiMPS aligner
  • counts reads associated to mature miRNAs
  • detects differential expression between two experimental conditions with DESeq2
  • detects changes in 3P/5P ratio for the same miRNA within two different conditions using RankProd statistics

An example data set is provided in BaseSpace that can be used with this App or the Small RNA v1.0 App.

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