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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: NGS

[Array Studio Video Tutorial] RNA-Seq Analysis Basic functions: Reads Quantification, Exon Junction and Gene Fusion Detection

Vivian Zhang

RNA-Seq has become one of the most popular methods in gene and transcript level genomic research. It could help quantify gene and transcript expression, identify sequence variants and detect gene, transcript or exon level genomic events. Array Studio provides a variety of functions powerful enough for small and large scale genomic research. In this article, we will introduce a few basic and the most commonly used functions, including sequence quantification, gene annotation, exon junction detection and gene fusion detection. 

 

 

ArrayStudio provides a number of modules and options for RNA-Seq quantification at gene, transcript, exon and exon junction levels. Both FPKM and Count tables can be generated. 

Example RNA-seq gene count table and its corresponding design table.

Example RNA-seq gene count table and its corresponding design table.

 

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 the Land products, we provide modules and visualization functions that make it easier for users to research splicing. In RNA-Seq analysis, besides gene and transcript counts, Array Studio can report exon junction counts as well. Results can be visualized in Omicsoft's Genome Browser.

Exon junction report and genome browser view.

Exon junction report and genome browser view.

Mutation data allows user to compare mutation frequencies and research individual variants. Users can run the  Summarize Variant Data module to annotate variants. Variants can be annotated in Mutation Reports or VCF files, and visualized directly in the Genome Browser.

Mutation annotation report and example genome browser view of variant V600E. 

Mutation annotation report and example genome browser view of variant V600E. 

 

 

Fusion genes can play an important role in cancer mutations that have multiple effects on a target gene. At Omicsoft, we provide a powerful fusion detection algorithm in FusionMap. FusionMap identifies unmapped reads that span multiple genomic locations, indicating possible gene fusion events:

Map Fusion Reads module will detect fusion genes from fusion junction-spanning reads which can characterize fusion genes at base pair resolution. This works with single end or paired end data. Combined Fusion Analysis will run fusion junction spanning + inter-transcript fusion read pairs detection at the same time. It detects fusion junction spanning reads from unmapped reads in BAM files, and detects inter-transcript fusion read pairs from singletons from BAM alignment entries. It will return a report showing potential fusion genes and counts for each fusion junction  Combined fusion analysis can only be run on paired-end data. 

Fusion report reports fusion count data with fusion annotation information attached.   Fusion genome browser can display sequence information at base pair resolution  . 

Fusion report reports fusion count data with fusion annotation information attached. Fusion genome browser can display sequence information at base pair resolution

 

 

[Feature Review] Comprehensive Quality Control of Next Generation Sequencing Data

Vivian Zhang

Next-generation sequencing (NGS) technology is revolutionizing genomic research. NGS has become one of the most commonly used methods in genomic and even clinical research. With  increased data output capacity and dramatically dropped costs associated with it, researchers are producing trillions (TB) of base pairs of data everyday. With the large amount of data, data quality control is always critical to ensure the quality and reliability of the data. Omicsoft's NGS analytics provides comprehensive functions for NGS raw data and aligned data QC, both for DNA-Seq (Exome-Seq, WGS, and targeted sequencing) and RNA-Seq. 

[NGS RAW DATA QC]

In Array Studio, the NGS Raw Data QC Wizard is an easy-to-use choice to run multiple QC commands simultaneously. The Raw Data QC Wizard provides options including Basic statistics, Base Distribution, Quality BoxPlot, K-Mer Analysis and Sequence Duplication.  

The Basic Statistics module generates some simple composition statistics for the files analyzed, such as sequence length, GC content etc. The NGS Base Distribution module can be used to check for uniformity between the different bases, as one would expect to see about equal distribution of the four bases across the length of the read. The Quality BoxPlot module is used to look at the quality score for each base pair in a file (aggregated over all reads from that file). It gives the user an idea of where the quality score starts to drop off for each file. The "K-Mer Analysis (K=5)" module counts the enrichment of every 5-mer within the sequence library. It calculates an observed/expected ratio for each k-mer based on the base content of the library as a whole and then uses the actual count that the k-mer appears. This can help find over-represented sequences which are not aligned in the data.

[SEQUENCING ALIGNMENT AND ALIGNED DATA QC]

After raw data QC, the user can move forward to the next step in his or her NGS analysis with more confidence in the result. The user can use Omicsoft Sequencing Aligner (OSA) to align the data to the genome of choice. OSA (Omicsoft Sequence Aligner) is a fast and accurate alignment tool for NGS data. OSA is the base aligner for RNA-Seq, DNA-Seq, miRNA-Seq data in FusionMap, Oshell, and Array Suite (ArrayStudioand ArrayServer).

Figure: Percentage of alignment reads that match to 10 million 100bp paired ends simulation data with 0%, 0.5% (default), 1% and 2% error rates. Gene model provided (left) and not provided (right).

Figure: Percentage of alignment reads that match to 10 million 100bp paired ends simulation data with 0%, 0.5% (default), 1% and 2% error rates. Gene model provided (left) and not provided (right).

Figure: Alignment job run time of 10 millions 100bp paired ends simulation data with 0%, 0.5% (default), 1% and 2% error rates. Gene model provided   

Figure: Alignment job run time of 10 millions 100bp paired ends simulation data with 0%, 0.5% (default), 1% and 2% error rates. Gene model provided

 

However, even with an accurate aligner like OSA, it is important to examine the aligned data quality. Omicsoft provides comprehensive DNA-Seq QC Metrics and RNA-Seq QC Metrics. These metrics include alignment metrics, coverage metrics, duplication metrics, insert size metrics, flag metrics, profile metrics and more. A total number of more than 100 metrics ensures that the aligned data is fully examined and ready for downstream analysis. An example list of metrics of RNA-Seq data can be found: Aligned data QC.