Creating a Bulk RNAseq Series Report

How to create a series report to explore large cohorts of bulk RNAseq data

Prior to working with a series report, ensure that you have set up your library and created a series. Learn more about setting up your library here. 

Sample gene count files are required to work with the bulk RNAseq series report. Upload sample gene counts to the library or run a bulk RNAseq pipeline to generate the sample gene count files on the platform. 


Step 1. Go to your workspace and select the "Series Report" tab. Create a new series report- provide a name, description, select a series and the BioBox bulk RNAseq Dashboard

Series Report creation final

Step 2. Create a contrast. A contrast will generate the differential expression, gene count and GSEA files that can be visualized in your dashboard. 


Provide a name, specify the species, and select "Total RNAseq" for the experiment type. 

Screen Shot 2023-02-16 at 5.02.42 PM

Name each group and select Record or Experiment properties from your Library to subset your experiments. For example, you may have a series of 100 experiments from breast cancer patients and you would like to create a contrast comparing your patients with the TP53 mutation to your Normal patients. You can add as many properties as you like to narrow down your experiments

Contrast creation-1

On the following page you will see a list of experiments that match your filter criteria. If any of your experiments have more than 1 sample gene count file, you will be prompted to select the file to be used in this contrast. Use the checkbox to select the file you would like to move forward with. 

contrst file confirmation

Submit the contrast creation pipeline and wait for the data to be generated. The progress of the pipeline can be seen on the "Data" tab. Once the pipeline is complete, you can load the data into each widget and explore your observations 


Navigating your series report 

Pathway enrichment widget

Select a contrast, database, and apply filters to visualize your data. This widget is using the differential expression file generated in the contrast which will enable you to filter on the log2 fold change and P adjusted value.

pathway enrichment, select database + contrast

Filter your data

The filters applied will subset the gene list from the differential expression file. For example if you apply the filters log2 fold change > 4 and P adjusted value  < 0.05, all genes that satisfy that filter criteria in the contrast you have selected will be used to generate your pathway enrichment. 

Pathway enrichment filter data

Explore your data

Select a bar corresponding to a pathway to see all of the genes enriched in the contrast you have created + filters you have applied. Select a gene to obtain a description of the gene. If you have generated multiple contrasts, swap between contrasts and apply different filters. 


Heatmap widget 

Select a contrast to visualize your data, use the right hand bar or select a gene cluster to zoom into a specific region of the heatmap


Explore your data

Select "Explore Data" to customize your heatmap. Any customizations that you make will be reflected on the dashboard. Learn more about how to customize your heatmap here.


Gene Set Enrichment 

Select a contrast, any collections and gene sets that are enriched in your data will be available for exploration

GSEA widget

Explore your data

Select "Explore your data" to obtain a full summary of your Gene Set Enrichment. This includes a summary of your results, gene table, and heatmap of the genes enriched in each gene set. 

Observation Search

Search for a specific gene and explore observations across all datasets on the platform. 

Type in a gene and select the type of observation you would like to see. Scroll through the plots to see your observations. Narrow down your results by searching for a specific record or file. 

pathway enrichment, select database + contrast