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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 Category: Newly implemented feature

[New Feature] Manage Land Sample Clinical Data

Vivian Zhang

Omicsoft has been working diligently over the past few months to both strengthen our ability to incorporate clinical data, as well as  growing our list of curated clinical measurements from public datasets. Currently, there are more than 1000 different clinical measurement variables in total, including sample demographics, survival data, symptoms, treatments and more in OncoLand and DiseaseLand. Moreover, users often have their sets of internal clinical data they wish to add to the system. If you have not started leveraging the power of our clinical data subsystem, please take a look at OncoLand Case Study - Clinical Variables for a 10 mins quick video tutorial on how to utilize clinical data to identify novel associations.

To help users better manage Land clinical data, we recently implemented Manage Sample Clinical Data function in Land. This function can be accessed through:

 

 

This function allows users to add clinical data, manage clinical variable meta data, remove samples and remove clinical vatiables: 

Add Clinical Data

Add Clinical Data

Adding clinical data is straightforward. In addition, "Metadata" for clinical data columns can be controlled by adding a second table. For example, clinical data column grouping can be controlled by a table where the first column contains Clinical Data column names, and the second column contains category:

Add Clinical Variable Metadata

Add Clinical Variable Metadata

 

The function is easy-to-use and straightforward, allowing users to manage their clinical data efficiently and effectively. For more details on the function, please refer to our wiki page

Stay tuned for additional functionality coming at the end of this year, including support for CDISC formatted files, to include time-series measurement data.

[New Feature] Geneset Analysis Updates: Enrichment Score, Volcano Plot and Summary Bar Plot

Vivian Zhang

Early this fall, Omicsoft released the new Geneset Analysis functonality (See webinar  Announcing GeneSet Analysis Functionality, integrated with Omicsoft’s Land databases and blog post Geneset Analysis Functionality: Integrated With Omicsoft Land Databases.). It helps users to identify comparisons containing similar gene set enrichment from both tens of thousands of gene sets in the Lands as well as customer gene sets, with directional results. Geneset Analysis is under active development, and we would like to update you with a few new features since its release.

GeneSet Analysis result

GeneSet Analysis result

 

Gene Set Enrichment Analysis Report
 

The Geneset Enrichment Analysis Report reports p-value, enrichment score, direction of enrichment and other annotation information:

Geneset Enrichment Analysis Report

Geneset Enrichment Analysis Report

 

Enrichment Volcano Plot

 

Enrichment Volcano Plot is a plot of Enrichment Score vs P-Value. The Enrichment score for the gene set is the degree to which this gene set is overrepresented at the top or bottom of the ranked list of genes in the comparisons. The plot helps to visualize potential gene sets of interest to further research on, with indication of enrichment directions. 

Enrichment Volcano Plot

Enrichment Volcano Plot

Summary Bar Plot

The Summary Bar Plot helps to visualize the number of overlapped genes and dynamically links to those genes with details in details window.

Summary Bar Plot

Summary Bar Plot

 

If you an Omicsoft Land customer, give it a try with the latest Array Suite version. Let us know any comments or suggestions you have!

[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. 

 

 

[FEATURE UPDATE]IMPROVED TIERED DATA MANAGEMENT CONTROL MAKING DATA SECURE

Vivian Zhang

As Omicsoft continues to experience increasing demand for customers to host clinical and patient data (both non-omic and genomics data), we constantly improve our data security and management functionality. We are in the process of evaluating our compliance with more rigorous federal regulations on top of our daily efforts to improve features one at a time (Stay tuned for our upcoming compliance document update). Among them, one recent improvement makes it possible for tiered data access control.

To illustrate, for example, a client may have research project portfolio as follows stored on Array Server:

Example client research project portfolio.

Example client research project portfolio.

In this case, the main folders represent disease areas, which each has multiple sub folders corresponding to different clinical trial projects. As Array Studio administrator or manager, controlling user access to different research projects is critical. Previously, Omicsoft enables control of user access to a main folder but not sub folders. Thus, administrators have to create one main folder for each project or group projects that has exactly the same control structure, if they didn't want additional people to have read or edit access. Now, with the improved tiered folder control, administrators can control read and edit access of each single folder. In this way, projects can be easily grouped by disease areas, departments, locations or any category of preference that is suitable on a client by client basis. Moving forward, clients can and should continue to utilize Array Studio as their genomics research project management hub to not only analyze but also manage all genomics projects. 

For more detailed information, please contact us about how to better manage project and access on Array Server.

[New Feature] Exon Junction Curve in Genome Browser to Show Exon Junction Curves Side by Side with Coverage

Vivian Zhang

Alternative Splicing (AS) is a process that exons or noncoding regions within DNA are differentially skipped or joined, resulting in different protein isoforms. This process allows individual genes to encode different mRNAs that encode proteins with diverse and even opposite functions. Alternative splicing has been shown to play an important role in a number of human diseases, including cancer, cardiovascular and neurodegenerative diseases. In Omicsoft Array Studio and Land, we provide modules and visualization functions that make it easier for users to research splicing. One example is the recent implemented function, Show Exon Junction Curve in Omicsoft Genome Browser.

Previously, in Omicsoft Genome Browser, we provide Exon Junction information in each individual track: 

Lung adenocarcinoma sample RNA-Seq data in Genome Browser. The blue lines below the read signal and the numbers indicate the number of exon junction reads. 

Lung adenocarcinoma sample RNA-Seq data in Genome Browser. The blue lines below the read signal and the numbers indicate the number of exon junction reads. 

The Show Exon Junction function allows user to checkout the number of exon junction reads. To better improve the visualization especially in the case of alternative splicing, we implemented Exon Junction Curve function:

Lung adenocarcinoma sample RNA-Seq data in Genome Browser with Exon Junction Curves. The LUAD track represents all lung adenocarcinoma samples. The Solid Tissue Normal and Primary Tumor tracks represent the normal and tumor sample from lung adenocarcinoma subject respectively. 

Lung adenocarcinoma sample RNA-Seq data in Genome Browser with Exon Junction Curves. The LUAD track represents all lung adenocarcinoma samples. The Solid Tissue Normal and Primary Tumor tracks represent the normal and tumor sample from lung adenocarcinoma subject respectively. 

Exon Junction Curve provides better visualization of exon junction events. In above example, it clearly shows the alternative splicing in lung adenocarcinoma samples (Two curves in LUAD track). The height of the curve represents the number of reads scaled to the total reads within the same track. In contrast,  the Solid Tissue Normal and Primary Tumor tracks only have one exon junction curve for each track, implying that differential splicing of PMP22 occurs in tumor and normal samples. 

 

 

[New Feature] Improved Visualization: PCA Ellipse

Vivian Zhang

Principal components analysis (PCA) is commonly used for clustering gene expression data. It allows us to cluster genes based on the different conditions, such as treatment and control, drug responses, time points etc. With new Array Suite 9.0 release, we improve our PCA visualization by adding PCA ellipse to display PCA confidence level. 

 

As an example, let's look at the gene expression data from two different case and control groups. A 2D PCA on the dataset: 

2D PCA on case vs control dataset. There are three ellipses representing 3 confidence regions: The black ellipse for all samples, the blue ellipse for case samples and the green ellipse for control samples.  

2D PCA on case vs control dataset. There are three ellipses representing 3 confidence regions: The black ellipse for all samples, the blue ellipse for case samples and the green ellipse for control samples.  

The confidence level indicated by the ellipse helps user to better "visualize" the confidence of the clustering. 

[New Feature] New Violin Plot for Variable View in Array Suite 9.0

Vivian Zhang

A violin plot is a method for plotting numeric data. It is similar to box plot, but additionally shows the probability density of the data. Violin plot is commonly used in displaying variable data, for example, gene expression data. In Array Suite 9.0, we implemented the violin plot function for all variable views, including the ability to create Land views with this gallery type.. 

Image: Violin plot of Gene FPKM for EGFR by Tumor Type. Data from OncoLand TCGA2015.

Image: Violin plot of Gene FPKM for EGFR by Tumor Type. Data from OncoLand TCGA2015.

[Feature Update] New Array Studio Launcher Accelerates Software Download

Vivian Zhang

Quick Announcement: Recently, Omicsoft released a  new version of Array Studio Launcher (http://www.omicsoft.com/software/ArrayStudioLauncher/publish.htm). By launching Array Studio, the new software loading page displays:

The new Array Studio Launcher is 10 times faster in downloading software upgrades, saving up to several minutes downloading time.

[New Feature] Columns/levels/rows reorder in Land Made Easier

Vivian Zhang

At Omicsoft, we continue to expand and improve variable annotation, meta data and clinical measurement to provide data as comprehensive as possible. For example, in Land, a table or variable view may have hundreds of columns. 

In this case, being able to flexibly order and display columns, rows or levels becomes important. Recently, we improved our columns/levels/rows reorder functions in Land. For example, when the user wants to specify columns:

When there are multiple or even hundreds of listed columns, previously the user could only reorder a specific column one position at a time by clicking the up and down arrows. Now, we implemented two additional buttons that allow the user to move a column to the top or bottom of the list by one click:

By clicking the highlighted buttons, the user can move the selected column up to the top or down to the bottom.

Reorder window after.png

At Omicsoft, we believe that customer-oriented product design with attention to details determines excellence.



[New Feature] Sample filtering made easy with new String Filter function

Vivian Zhang

At Omicsoft, we have a continually growing Land user base. The increasing number of public genomic research projects and datasets has made it possible to research on public samples with certain disease, gene mutation or clinical phenotype without spending millions of dollars to conduct the experiments. As we continue to improve Land sample search and filter capacities, we are glad to introduce a new String Filter function that will make it easier to search multiple samples, genes or any conditions. 

For any string variables, no matter it is sample ID, gene name, clinical measurement or others, the user can filter multiple strings using Add String Filter function:

For example, if the user is interested in gene expression of EGFR gene and wants to further research on a few samples with high EGFR expression in breast cancer, he or she will likely check the gene FPKM view of EGFR gene in TCGA Land and identify a few samples:

Samples with high EGFR expression in breast cancer patients are highlighted in pink.

Samples with high EGFR expression in breast cancer patients are highlighted in pink.

Next, the user can right click on SampleID filter, as it is shown in Figure 1, and choose Add String Filter (Select) to select sample ID names:

Or, the user can choose Add String Filter (Input) and just copy in the sample ID:

The string filter function applies to all string variable filters. Now, let's get started with fast string filtering on your sample of interest!

Note: Array Studio version requirement: v8.1.0.95  or higher.

[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.

[GENOMIC RESEARCH] Mutation Analysis with improved mutation annotation system

Vivian Zhang

Identifying disease associated gene mutations is an important part of genetic disease research in designing of targeted drugs. To accelerate gene mutation analysis, Omicsoft's Land database provides rich mutation visualization views including mutation and somatic mutation site distribution, mutation landscape, and mutation genome browser.  Omicsoft's recent improvement to it's mutation annotation system allows user to annotate and filter mutations based on hundreds of criteria, including mutation confidence, position, gene information, functional mutation, eQTL information, regulation information protein information, and clinical information, using publicly available databases as the source for annotation. 

Land mutation annotation directory

A simple example is to compare the mutation distributions with and without synonymous mutation included:

Figure: TP53 mutation distribution with synonymous mutation included

Figure: TP53 mutation distribution with synonymous mutation included

Figure TP53 mutation distribution with synonymous mutation excluded

Figure TP53 mutation distribution with synonymous mutation excluded

With an improved annotation system, the user can also filter mutation and identify clinical phenotype associated mutations, using database resources like ClinVar.

Databases additionally include SIFT, Polyphen, 1000 Genomes, ExAC, ESP6500, GTEx eQTL, RegulomeDb, and Interpro Domain, and the system is designed to be able to support countless other databases or customer's internal annotation systems as well.

Figure: TP53 mutation landscape in Li Fraumeni Syndrome samples

Figure: TP53 mutation landscape in Li Fraumeni Syndrome samples

[Newly implemented features] Show Query Status-Audit Your Queries in Land

Vivian Zhang

Omicsoft has rapidly expanded it’s Land (OncoLand and ImmunoLand) datasets, and with sample/patient information being increasingly important, it is crucial to be able to navigate and filter sample information in order to fine tune the data visualizations. We aim to provide extremely detailed sample and clinical information.

With the powerful sample query abilitiy and hundreds of clinical annotation items available, it may be hard to remember and trace back all the customized filters and queries.

To help navigate through the sample and clinical information jungle, Omicsoft has added a new feature: Show Query Status. 

With this feature, you don’t need to worry about being interrupted when navigating the data and forget about what filters you applied. The Show Query Status function will record it all for you.  You can use this information when creating presentations, taking notes for your research, or just as a way to ensure you know what filters are applied to your current search query.

Navigate through the jungle faster and replicate your success path!