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Overview

Omicsoft is the leading provider of Next Generation Sequencing, Cancer Genomics, Immunology, and Bioinformatics solutions for Next Generation Sequencing Data and Gene Expression Analysis.

Exciting Updates and Latest News

Keeping you up-to-date with the latest in NGS, Bioinformatics Analysis, and cancer genomics with blogs on Array Suite, OncoLand (TCGA and more), ImmunoLand, and more.

Filtering by Tag: ImmunoLand

[New Feature] Geneset Analysis Functionality: integrated with Omicsoft Land databases

Vivian Zhang

Gene Set Analysis is a powerful tool to help users who have their own gene signatures and would like to identify comparisons or other signatures containing similar gene set enrichment from both tens of thousands of comparisons in the Lands as well as customer gene sets for on-premises customers. Recently, Omicsoft officially released our new GeneSet Analysis function. For more details, check out our webinar recording Announcing GeneSet Analysis Functionality, integrated with Omicsoft’s Land databases presented by Matt Newman, VP of Business Development at Omicsoft on September 28th, 2016. 

Previously, Omicsoft's Land system offered a simplified GeneSet Enrichment Analysis. It allowed users to compare their own gene sets with those contained in the Lands: 

Although this was powerful enough to identify comparisons with similar gene sets:

1. it was restricted within a specific Land of choice and not shared across Lands

2. it did not take directionality into account

3. it was not able to include other genesets beyond Land data as target gene sets 

4. it required the user to be familiar with the Land system, and not just the analysis sub-system of Array Suite.

Even though Omicsoft's Array Studio also provides a Molecular Signature module that allows users to compare to Broad's molecular signature database, the Molecular Signature module also does not take directionality into account and requires user to add straight lists to Array Studio Projects, with no ability to incorporate inference reports, nor any of the important data stored within the Lands or easily incorporate customer Gene Sets.

 

In order to more fully leverage Omicsoft's data assets, we have officially released our new GeneSet Analysis module. The new GeneSet Analysis allows the users to query across OncoLand, DiseaseLand, Molecular Signatures, and more. 

GeneSet Analysis Wizard

GeneSet Analysis Wizard

In addition to the geneset databases included, the new GeneSet Analysis also provides directional results -- up and down p-values and directions.

GeneSet Analysis result

GeneSet Analysis result

We are still in active development of the GeneSet Analysis module, constantly improving our content, functions and visualizations. Here are a couple examples we are working on:

1. Multi-species data support in addition to human and mouse data

2. Additional visualizations based on table results

If you have any comments or suggests, please let us know. 

 

Want to give it a try? Please check out our latest webinar Announcing GeneSet Analysis Functionality, integrated with Omicsoft’s Land databases and our GeneSet Analysis wiki for detailed illustration. 

 

 

Bridging Bioinformatics|Genomics|Genetics Research: 2016 Omicsoft User Group Meeting

Vivian Zhang

 

  • Who Attended:
    • More than 30 leading pharmaceutical and biotech companies. 
    • More than 100 attendees who are experts and scientists in the field of bioinformatics/genomics/genetics.
  • What Occurred:
    • Numerous discussions among attendees on the future of biomarker discovery, as well as best practices of data management, visualization and analysis.

 

  

Omicsoft Corporation successfully held our kick-off Omicsoft User Group Meeting in Cambridge, MA on Wednesday May 4, 2016.

We would like to thank all speakers and attendees, all of whom are extremely important in helping build out our platform successfully.  We've received extremely positive feedback from the meeting, and hope to do it again in the future.  Feedback on our software and services help drive our business, and the direct interaction with our customers during the event proved invaluable to us. 

Highlights from the meeting:

  • Introduction of GeneticsLand for management of genetics data
  • Introduction to the future SingleCell Land
  • Overview on curation processes
  • Updates on current data subscription Lands

For more details, please visit our 2016 User Group Meeting webpage.

 

Above is just a glance of some exciting moments at our meeting. If you missed the meeting, we have uploaded our speaker presentations and videos on our 2016 User Group Meeting webpage.

If you have any question with regard to the meeting, please contact us. 

 

[New Feature] ImmunoLand Update: Viewing Expression Level of Multiple Genes (Gene Pathway) through Multigene Variable View

Vivian Zhang

Genetic diseases are often results of malfunctions in multiple genes or gene pathways. Being able to understand the correlation between genes or to compare multiple genes is crucial in genomic research. At Omicsoft, we try to provide multiple gene views and pathway views to make researcher's life easy. In the recent released ImmunoLand, a new Multigene Variable allows user to view gene expression level of multiple genes of interest in the same chart.

Previously, ImmunoLand provides view for gene level and transcription level expression of single gene:

Transcript FPKM of EGFR categorized by disease category. 

Transcript FPKM of EGFR categorized by disease category. 

Now, a new multigene variable view is available:

Gene FPKM of SLC35E2B, BCAS3, BTRC and EYA1.

Gene FPKM of SLC35E2B, BCAS3, BTRC and EYA1.

The user can further specify multiple grouping categories:

Gene FPKM of SLC35E2B, BCAS3, BTRC and EYA1 grouped by disease category.

Gene FPKM of SLC35E2B, BCAS3, BTRC and EYA1 grouped by disease category.

[Feature Review] Analyze "Land" Genomic Data with the R API

Vivian Zhang

Omicsoft's current Lands, OncoLand and ImmunoLand, provide users pre-configured data content covering a variety of genomic data types. The rich visualization capacity and customizable filters empower Lands to be comprehensive OMIC data hubs. Many of our customers process their own in-house data into our Land format, either themselves, or by contracting us to run the datasets for them (we do everything from RNA-Seq to WGS data so contact us at sales@omicsoft.com if you would like to contract out some data processing.)

That said, in the world of research, there are always talented and creative bioinformaticans that would like to explore the data in their own way. Our Land R API function provides a way to query Land data using R. 

The R API function uses Oshell API functions to connect to ArrayServer and run the Land Text Dump function on a list of genes or/and on a list of samples. User can run additional analysis based on the land dump data in R and create more data visualizations, customized to their liking.  Once the data is in R, the analyst has the world of Bioconductor and more with which to work with for their analysis.  Enjoy!

Example 1: Scatter plot of expression value vs. CN log2ratios within specific genes and samples

An example to draw scatter plot of gene expression vs. CN log2ratios for genes MDM, BRAF, EGFR, and FGF12

An example to draw scatter plot of gene expression vs. CN log2ratios for genes MDM, BRAF, EGFR, and FGF12

Example 2: Scatter plot of expression value vs. CN log2ratios with full sample meta data

[Feature Review] Save Customized Views for Future Usage and Sharing through in the "Lands"

Vivian Zhang

In Omicsoft's Lands (ImmunoLand and OncoLand), we have pre-configured over 40 views for different data types, including RNA-Seq, DNA-Seq, miRNA-Seq, Copy Number Variation, Gene Expression Chip, Protein Expression, Methylation and hundreds of clinical measurements. While we design our Lands to be extremely powerful in providing visualizations with customizable gene, sample and project filters along with customizable graphical designs, we acknowledge that it sometimes takes time to explore the data. For some of our customers, admin/super user want to configure their company or group specific views. Or, users in a specific research group may want to set customized views that are most commonly used for a specific disease or project. All these customization can be done through the Land custom view format.

How many steps does it take to display the expression of gene POLR3A at difference stages of systemic sclerosis comparing to normal control in study GSE58095? To draw the plot like the one below, the use needs to search the gene POLR3A, click on Expression | Expression Intensity view, filter project GSE58095, change grouping to disease category and make sure the color and scale are of the preferred settings. 

Expression Intensity of POLR3A in different stage of systemic sclerosis in study GSE58095.

Expression Intensity of POLR3A in different stage of systemic sclerosis in study GSE58095.

After the user has made it to this view and feels it can be potentially very informative for his or her project, the user can save the view: 

Furthermore, if the user wants to share to view with the whole team and would like to replicate this query for other genes or projects, the user can ask the admin to create custom views. To see how to create customer views in land, please check out our wiki page: Custom Views in Land or contact us. As a standard user, the query can be set up as Custom Views, or even be grouped into a selection of custom views into specific project folder, like this one for Scleroderma Projects:

Creating your own Lands for integration with OncoLand or ImmunoLand

Matt Newman

Free Land Creation

While many of our users are aware of the OncoLand and ImmunoLand datasets, not everyone might be aware of how easy it is to create your own Lands, and further integrate these with the public Lands (for instance with TCGA).

Omicsoft provides easy-to-use command line tools that can be used to import your own mutation data, copy number data, and RNA-Seq data into a Land created specifically for you or your dataset.  These can then easily be combined with "virtual" lands to create a Land that allows visualization and querying of your data side-by-side with the public data. In order to do, curation is the key requirement, as you must choose two columns for integration. In most cases, for OncoLand-based Lands, this will be Tumor Type and Sample Type (Primary Tumor, Normal, etc.), and for ImmunoLand this might be DiseaseState and Tissue.

These tools are available for free with your subscription to either OncoLand or ImmunoLand, and if you'd like to try building the Lands yourself, contact support@omicsoft.com with any questions on getting started.

Paid Land Creation

Many of our users prefer to have Omicsoft do the Land creation, including processing of their data through our pipelines (using either Omicsoft resources or the customer resources via VPN access).  This can be a way to get the benefit of internal Land creation, without having to invest any time in gaining expertise on how the process works.  If you're interested in seeing how we can help process your data, be it WGS, WXS, Targeted Sequencing, RNA-Seq, and more, contact us at sales@omicsoft.com.

Finding Association to Clinical Variables

Matt Newman

Association of clinical variables in Cancer Genomics or Immunology

One question we've had come up many times, whether it's in the context of cancer genomics with the TCGA dataset in OncoLand, or in the context of ImmunoLand and project-specific clinical variables, or even for your own datasets where you have many clinical parameters, is how to quickly scan all clinical variables, based on some prescribed grouping, and find the variables that are most significantly associated with that grouping.

Imagine we have a population of samples (let's say patients with Colon Adenocarcinoma) and we'd like to know - what clinical variables in the TCGA dataset correlate with that status?  For instance, what clinical variables correlate with BRAF V600E mutation status in these samples?

I'm pleased to announce that we now have that ability, using the new Group Association view, available at the top level of every Land.

Microsatellite Instability (MSI) found to correlate with BRAF V600E mutation status in colon adenocarcinoma samples.

Microsatellite Instability (MSI) found to correlate with BRAF V600E mutation status in colon adenocarcinoma samples.

As you can see from the screenshot, MSI status (Microsatellite instability) correlates with BRAF V600E status in Colon Adenocarcinoma samples.  A quick search of the literature finds similar conclusions: http://www.ncbi.nlm.nih.gov/pubmed/23878352.

A search for mutations in BRAF confirms the larger population of MSI-H samples vs other MSI status types in colon adenocarcinoma.

A search for mutations in BRAF confirms the larger population of MSI-H samples vs other MSI status types in colon adenocarcinoma.

With thousands of clinical variables available in TCGA and other datasets, this new functionality opens up the data mining possibilities for users interested in looking at clinical data side-by-side with OMIC data.

[IMMUNOLOGICAL RESEARCH] Research an Immunological Genome Study in ImmunoLand

Vivian Zhang

Traditionally immunology studies are focused on a particular protein or pathway. However, immunological activity is a system-level response, which is well suited for large-scale integrative approaches and requires an overall perspective on the immune system(s). With advanced technologies enabling large-scale, genome-level approaches, immunology studies are embracing the era of immunogenomics (Related Readings: Beyond the transcriptome: completion of act one of the Immunological Genome Project. ).

ImmunoLand is Omicsoft's most recently developed Land database. It is an immune-related genomics database and visualization software that helps users explore public and private immune-focused genomics datasets. In ImmunoLand, researchers can search a gene, multiple genes, a pathway, a project or multiple projects across more than 22,000 samples from public projects, including GEO (Gene Expression Omnibus), SRA (Sequence Read Archive), ArrayExpress, dbGAP (The Database of Genotypes and Phenotypes), and other large data repositories like BluePrint, GTEx, and ImmGen (The Immunological Genome Project). 

Here is how:

Immunological genomics studies are currently conducted based on many different diseases, immune cells, activation responses, treatments, tissues, states of cell differentiation and so forth. In ImmunoLand, each study in the database is carefully reviewed by Omicsoft’s curators, with meta data clean-up occurring, outliers removal, and then statistically-driven comparisons generated for each study. ImmunoLand allows the users to be able to search across projects, or search directly for a project of interest. For example, let's search for the project GSE37448 from the Immunological Genome Project:

Figure: Gene Expression Intensity Heatmap categorized by disease category

Figure: Gene Expression Intensity Heatmap categorized by disease category

By default, the view is displaying a heatmap of the expression intensity of samples, categorized by disease category. It is interesting to look at the heatmap of the genes with highest differential expression across cell types: 

Figure: Gene Expression Intensity Heatmap of genes with Gene Rank Expression Intensity <100

Figure: Gene Expression Intensity Heatmap of genes with Gene Rank Expression Intensity <100

Figure: Expression Per-Gene View showing gene CD3G

Figure: Expression Per-Gene View showing gene CD3G

Next, the user can search for their gene(s) of interest across projects to compare different comparisons (diseases, immune cells, activation responses, treatments, tissues, states of cell differentiation). The GSE37448 study was done in mouse. It might, for instance, be interesting to check out the gene expression in human organs in ImmunoLand2015 instead of ImmunoMouse2015.

 

OncoLand and ImmunoLand Update Webinar (Updates to TCGA and GEO Datasets)

Matt Newman

Jack Liu, President of Omicsoft, will discuss and demonstrate live some of our biggest updates to the “Land” technology since its introduction in 2013. This includes framework updates, feature updates, as well as data updates to both OncoLand and ImmunoLand. 

Major framework updates: 

(1) deep clinical integration with the user interface and analytics with carefully curated TCGA clinical data 
(2) dynamic correlation framework providing instant integration capabilities across different data types and genes 
(3) much improved comparison support greatly enhancing our ImmunoLand subscription and future OncoLand subscriptions 
(4) integration with our breakthrough variant annotation system. 

Also included are the following features/data updates: 
(1) Built-in metagenomics integration (viral, bacterial) for TCGA, GTEx and a few other “Lands” 
(2) Sample specific views (expression, CNV and mutation) 
(3) Grouping/Profiling visualization support for multiple columns 
(4) Various “GeneSet” view improvements, including performance improvement 
(5) Cross-tissue normalized protein data: RPPA-RBN 
(6) New “Group Summary” views for powerful exporting of statistics behind the boxplots, heatmaps, etc. 
(7) Thousands of new NGS and MicroArray samples for ImmunoLand with additional disease coverage 
(8) Various data updates (TCGA, ICGC, GenetechCellLine, etc.) for Oncoland 

We will also present some of the near-future working projects, including HLA typing and dynamic cohort support. The Land updates will also be made available to our customers on July 17th as well.

We'll also update our blog in the coming days with direct links to the recorded webinar, and stay tuned for blog posts showing some of the newly released features and datasets.

[GENOMIC RESEARCH] Identifying Alternative splicing in ImmunoLand

Vivian Zhang

Alternative splicing is a regulated process during gene expression that can produce variant proteins from a single gene. It plays an important role in cellular functions and is closely related to a variety of diseases (1). At Omicsoft, our Land products (ImmunoLand and OncoLand)  allow users to identify splicing events that are associated with diseases, pathological measures or any clinical information. 

Figure 1. Splicing of Serpinb7 in lesional versus non-lesional samples.  Different dominant transcripts express in lesional versus non-lesional samples, suggesting the association between serpinb7 splicing and lesion.&nbsp;

Figure 1. Splicing of Serpinb7 in lesional versus non-lesional samples. Different dominant transcripts express in lesional versus non-lesional samples, suggesting the association between serpinb7 splicing and lesion. 

Interesting in learning how to identify differential splicing, for instance the splicing event of serpinb7 in lesional and non-lesional psoriasis samples? Land Integration Analysis can help.

First, the user can group the SampleSet for the samples of interest using specific disease status, pathological measures or clinical information. Using our newly released ImmunoLand, the user can set the Grouping into Pathology, and then filter lesional and non-lesional samples for display. By selecting all lesional samples, the user can create Lesional Samples vs Non Lesional SampleSet.

Land Integration Analysis allows the user perform differential analysis on expression, splicing, copy number variation and mutation data using SampleSet. For example, by using lesional and non-lesional sample grouping, the user can perform integration analysis trying to identify the splicing event associated with lesional status:

The analysis result reports statistics of Kruskal-Wallis Test, the smaller the p-value (FDR adjusted) is, the stronger the splicing is associated with lesion. In this case, serpinb7 appears to be the top gene:

 

Next, the user can search serpinb7 in ImmunoLand, and then check out RNA-Seq | Genome Browser view, use Omicsoft's powerful Genome Browser functions to generate Figure 1 and visualize the splicing events. A brief search on PubMed shows other exciting work on serpinb7, suggesting its roles in keratosis and carcinoma.