OmicSoft DiseaseLand is the disease-focused platform designed to help you harness thousands of disease-focused datasets to accelerate biological discovery. Bringing together robust data visualization and analytics tools, OmicSoft “Land” technology rapidly connects you to the most relevant insights. Explore gene expression data at the gene, transcript, and exon level, as well as whole-transcriptome analyses of differential expression. Every project in DiseaseLand is carefully curated and processed through common pipelines, allowing you to quickly find the most relevant results across projects. DiseaseLand saves you valuable time and resources, enabling you to focus on your research.
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Unlike other mutation databases, HGMD mutations are backed by peer-reviewed publications where there is evidence of clinical impact—and the gold-standard, industry-leading resource just got better.
View the complete HGMD Professional statistics here.
When using Batch Search, the results table will now include a ClinVar column to the far right. This column will provide links to ClinVar records and list predicted classifications.
Read about the importance of having access to the most up-to-date and comprehensive database for human disease mutations in our white paper.
Learn how to take advantage of all HGMD’s features by watching our video tutorials available at our Resources Page.
New ANNOVAR databases are now available!
Learn more about how ANNOVAR can be used with HGMD for variant annotation.
Watch a recorded webinar featuring ANNOVAR here.
Genome Trax 2018.4 has updated tracks containing the 2018.4 HGMD release or all HGMD-related tracks.
Need a clinical genomic interpretation solution?
Look no further than QIAGEN Clinical Insight (QCI). Offering the highest level of interpretation transparency currently available on the market, QCI dynamically computes ACMG classification and AMP-tiering based on phenotype and clinical evidence. QCI incorporates knowledge from HGMD, CentoMD, over 30 public and proprietary databases, and over 2,000 scientific and clinical articles manually curated each month.
Kick start your year and sign-up for a free QCI demo here!
Microbes play essential roles in human, animal and plant health. Knowing the composition and diversity of a microbial community is the first step in understanding microbe-microbe and microbe-host interactions, revealing key players in health and disease and discovering major modulators. Next-generation sequencing in microbiome research has accelerated data generation and changed our perception of the complexity and structure of microbial communities. However, microbiome data sets are typically high-dimensional, adding further complexity to data analysis and processing.
In our white paper, “Characterizing the Microbiome through Targeted Sequencing of Bacterial 16S rRNA and Fungal ITS Regions,” we demonstrate the power of the CLC Microbial Genomics Module for investigating complex microbial communities.
We used the original data of Purahong et al.’s work from the April 2016 edition of Molecular Ecology “Life in the leaf litter: novel insights into community dynamics of bacteria and fungi during litter decomposition,” to analyse amplicon sequencing data for profiling microbial communities via clustering reads into operational taxonomic units. Purahong’s study explored the dynamic interplay of bacteria and fungi during leaf degradation over a one-year period in response to fluctuations in nutrient availability.
We demonstrate how the usage of our pre-configured CLC workflows can ease analysis on-boarding, reduce hands-on time, and ensure consistency and reproducibility in microbiome analyses.
Purahong W, et al. (2016). Life in the leaf litter: novel insights into community dynamics of bacteria and fungi during litter decomposition. Molecular Ecology 25, 4059.
