HGMD Professional 2022.2 is now available, expanding the world’s largest collection of human inherited disease mutations to 368,587 entries—that’s 6,354 more than the previous release.
For over 30 years, HGMD Professional has been used worldwide by researchers, clinicians, diagnostic laboratories and genetic counselors as an essential tool for the annotation of next-generation sequencing (NGS) data in routine clinical and translational research. Founded and maintained by the Institute of Medical Genetics at Cardiff University, HGMD Professional provides users with a unique resource containing expert-curated mutations all backed by peer-reviewed publications where there is evidence of clinical impact.
detailed mutation reports
new mutation entries in Q2 2022 alone
HGMD Professional is powered by a team of expert curators at Cardiff University. Data are collected weekly by a combination of manual and computerized search procedures. In excess of 250 journals are scanned for articles describing germline mutations causing human genetic disease. The required data are extracted from the original articles and augmented with the necessary supporting data.
The number of disease-associated germline mutations published per year has more than doubled in the past decade. As rare and novel genetic mutations continue to be uncovered, having access to the latest scientific evidence is critical for timely interpretations of NGS data.
View the complete HGMD Professional 2022.2 statistics below.
WATCH OUR WEBINAR ON DEMAND
How to streamline your variant classification workflow with HGMD Professional
In this on-demand webinar, our experts discuss how you can streamline your variant classification workflows with HGMD Professional through real-world examples.
Watch the webinar here.
Unlike new machine learning or artificial intelligence platforms that rapidly index millions of journal articles for mutations, HGMD Professional leverages human judgement and expertise—every catalogued mutation has been “touched” by a trained scientist to ensure accuracy, relevance, and context.
Learn more about the industry-leading database here, where you can explore features, watch videos, and request a complimentary 5-day trial.
HGMD Professional 2022.1 is now available, expanding the world’s largest collection of human inherited disease mutations to 362,233 entries—that’s 9,502 more than the previous release.
For over 30 years, HGMD Professional has been used worldwide by researchers, clinicians, diagnostic laboratories and genetic counselors as an essential tool for the annotation of next-generation sequencing (NGS) data in routine clinical and translational research. Founded and maintained by the Institute of Medical Genetics at Cardiff University, HGMD Professional provides users with a unique resource containing expert-curated mutations all backed by peer-reviewed publications where there is evidence of clinical impact.
detailed mutation reports
new mutation entries in Q1 2022 alone
HGMD Professional is powered by a team of expert curators at Cardiff University. Data are collected weekly by a combination of manual and computerized search procedures. In excess of 250 journals are scanned for articles describing germline mutations causing human genetic disease. The required data are extracted from the original articles and augmented with the necessary supporting data.
The number of disease-associated germline mutations published per year has more than doubled in the past decade (Figure 1). As rare and novel genetic mutations continue to be uncovered, having access to the latest scientific evidence is critical for timely interpretations of NGS data.
Figure 1. Mutation entries in HGMD Professional 2022.1. The number of inherited disease-associated germline mutations published per year has more than doubled since 2010 (within 10 years).
View the complete HGMD Professional 2022.1 statistics below.
WATCH THE JANUARY 20, 2022 WEBINAR ON DEMAND
How to streamline your variant classification workflow with HGMD Professional
In this on-demand webinar, our experts discuss how you can streamline your variant classification workflows with HGMD Professional through real-world examples.
Watch the webinar here.
Unlike new machine learning or artificial intelligence platforms that rapidly index millions of journal articles for mutations, HGMD Professional leverages human judgement and expertise—every catalogued mutation has been “touched” by a trained scientist to ensure accuracy, relevance, and context.
Learn more about the industry-leading database here, where you can explore features, watch videos, and request a complimentary 5-day trial.
The Winter 2019 Release of the Human Gene Mutation Database (HGMD) Professional is available, expanding the world’s largest collection of human inherited disease mutations to over 275,000 entries–that’s 11,699 more than the previous release.
HGMD Professional is the de facto standard resource for comprehensive coverage of published germline mutations in nuclear genes that underlie, or are closely associated with, human inherited disease.
A subset of the HGMD gross deletions has now been mapped to both builds of the reference genome (NCBI38/hg38 and legacy NCBI37/hg19). Due to the absence of accurate breakpoint data for most of these lesions, 3,348 entries have been mapped in this release. HGVS nomenclature is also provided for this dataset.
In addition to the standardized HGVS descriptions provided by HGMD, users can now view predicted HGVS nucleotide-level descriptions based on non-canonical RefSeq and Ensembl transcripts.
Founded and maintained by the Institute of Medical Genetics at Cardiff University in 1996, HGMD Professional provides users with a unique resource that can be utilized not only to obtain evidence to support the pathological authenticity and/or novelty of detected gene lesions and to acquire an overview of the mutational spectra for specific genes, but also as a knowledge base for use in bioinformatics and whole-genome screening projects. Unlike other mutation databases, HGMD mutations are all backed by peer-reviewed publications where there is evidence of clinical impact.
The number of disease-associated germline mutations published per year has more than doubled in the past decade (Figure 1). As rare and novel genetic mutations continue to be uncovered, having access to the latest scientific evidence is critical for timely interpretations of next-generation sequencing (NGS) data.
View the complete HGMD Professional statistics here.
HGMD Professional helps clinical testing labs analyze and annotate next-generation sequencing (NGS) data with current and trusted information. Unlike other mutation databases, HGMD mutations are all backed by peer-reviewed publications where there is evidence of clinical impact.
To get the most out of your HGMD Professional subscription, visit our Resources webpage for case studies, technical notes, and video tutorials. Or hear from Peter Stenson, manager of HGMD, in an on-demand webinar on how HGMD has empowered a generation of geneticists for precision medicine here.
Or hear from Peter Stenson, manager of HGMD, in an on-demand webinar on how HGMD has empowered a generation of geneticists for precision medicine here.
New ANNOVAR databases are also available.
Learn more about how ANNOVAR can be used with HGMD for variant annotation. Watch a recorded webinar featuring ANNOVAR here.
The Genome Trax™ update will roll out at the end of January, 2020. Updated tracks have been released with HGMD 2019.4 content for all HGMD-related tracks.
For labs looking to generate clinician-grade reports for germline or somatic NGS testing, QIAGEN Clinical Insight (QCI) Interpret reproducibly translates highly complex NGS data into standardized reports using current clinical evidence from the QIAGEN Knowledge Base, which consists of over 40 public and proprietary databases, including HGMD Professional.
Click here for a free demonstration of QCI Interpret.
The Fall 2019 Release of the Human Gene Mutation Database (HGMD) Professional is available, expanding the world's largest collection of human inherited disease mutations to over 269,000 entries--that's 6,278 more than the previous release.
HGMD Professional is the de facto standard resource for comprehensive coverage of published germline mutations in nuclear genes that underlie, or are closely associated with, human inherited disease.
Founded and maintained by the Institute of Medical Genetics at Cardiff University in 1996, HGMD Professional provides users with a unique resource that can be utilized not only to obtain evidence to support the pathological authenticity and/or novelty of detected gene lesions and to acquire an overview of the mutational spectra for specific genes, but also as a knowledgebase for use in bioinformatics and whole genome screening projects.
The number of disease-associated germline mutations published per year has more than doubled in the past decade (Figure 1). As rare and novel genetic mutations continue to be uncovered, having access to the latest scientific evidence is critical for timely interpretations of next-generation sequencing (NGS) data.
HGMD Professional helps clinical testing labs analyze and annotate next-generation sequencing (NGS) data with current and trusted information. Unlike other mutation databases, HGMD mutations are all backed by peer-reviewed publications where there is evidence of clinical impact.
Read about the importance of having the latest clinical evidence in our HGMD white paper.
To get the most out of your HGMD Professional subscription, visit our Resources webpage for case studies, technical notes, and video tutorials. Or hear from Peter Stenson, manager of HGMD, in an on-demand webinar on how HGMD has empowered a generation of geneticists for precision medicine here.
New ANNOVAR databases are also available.
Learn more about how ANNOVAR can be used with HGMD for variant annotation. Watch a recorded webinar featuring ANNOVAR here.
The Genome Trax update will be available late October 2019. Updated tracks have been released with HGMD 2019.3 Additional major updates include TRANSFAC® release 2019.3, and PROETOME™ release 2019.3.
For labs looking to generate clinician-grade reports for germline or somatic NGS testing, QIAGEN Clinical Insight (QCI) Interpret reproducibly translates highly complex NGS data into standardized reports using current clinical evidence from the QIAGEN Knowledge Base, which consists of over 40 public and proprietary databases, including HGMD Professional.
Click here for a free demonstration of QCI Interpret.
View all upcoming events here.
As of March 29, 2019, HGMD contains over 256,070 germline mutations--a major achievement in our understanding of rare and hereditary disease. For years, HGMD has been recognized as the defacto standard repository for heritable mutations. Curated by experts in the field of genetics, HGMD offers information you can trust, with an unrivaled breadth of coverage. The proof is in the numbers:
256,070 expert-curated, disease-causing germline variants
10,500+ summary reports listing all known inherited disease mutations
2,600+ peer-review journals mined by experts in the field of genetics
104,000+ peer-reviewed literature reports cited
14,500+ scientific publications cite HGMD
17,000+ new mutation entries per year
View the complete HGMD statistics
Mutations may now be viewed according to whether they have additional literature evidence (browse mutations - additional literature evidence). Categories include additional functional evidence, additional phenotypes and additional case reports.
To get the most out of your HGMD subscription, please watch the video tutorials available at our Resources webpage.
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.
Updated tracks have been released with HGMD 2019.1 content for all HGMD-related tracks. Additional major updates include TRANSFAC® release 2019.1, and PROETOME™ release 2019.1.
QCI Interpret for Rare and Hereditary Disease is clinical decision support software that provides current scientific and clinical evidence to classify variants according to ACMG and ACOG interpretation guidelines.
QCI Interpret connects you to HGMD, plus 25 additional public and propriety sources. The software provides you with an expansive variant bibliography with full transparency to the underlying evidence, enabling you report confidently and scale efficiently. Learn more
Structural variants affect large regions of the human genome and also play a significant role in gene expression (1, 2). They are typically detected with short Illumina or long PacBio reads, or a combination of both approaches. The new Advanced Structural Variant Detection (ASVD) plugin focuses on the short read approach, and is able to detect structural variants using short Illumina reads from whole genome sequencing (WGS). It supports the detection of the most frequently occurring structural variant types in the human genome such as deletions, duplications, and insertions (1).
The ASVD plugin checks read mappings for evidence of breakpoints using “unaligned end” signatures. “Unaligned end” refers to the end of a read that does not map to the reference sequence. At biological breakpoints, it is expected that multiple reads display unaligned ends, giving rise to a signature. A statistical model evaluates the likelihood of each breakpoint based on the probabilities of supporting reads. Breakpoint signatures and coverage information are next processed together in a series of steps. These include specialized alignment algorithms, copy number variation (CNV) detection, and local de novo assembly. If multiple structural variant calls are based on the set of breakpoints, the optimal calls given the breakpoint evidence are reported as the final set of detected structural variants.
Detected breakpoints and structural variants can be viewed together with the read mappings and the reference sequence. Track tables can then be used to filter and select individual breakpoints and structural variants as shown in the example in Figure 1.
Figure 1. Genome track view of the reference sequence, the read mapping of the sample and a track with the structural variant calls. The table view of the structural variant calls track allows interactive filtering and viewing of the results. An example of “unaligned ends”, i.e. ends of reads that do not match the reference genome, are seen as transparent ends of lines representing reads in the mapping.
To evaluate the performance of the ASVD plugin, we compared it to Illumina's Manta. Recent benchmarks against Delly and Lumpy showed that Manta had superior performance (3, 4).
We made use of two recent data sets from Huddleston et al. (5) and Shi et al. (6) to evaluate the ASVD plugin and Manta. Both of these studies used PacBio reads for contig assembly and structural variant detection concerning the GRCh38 reference.
While Shi et al. utilized a diploid genome from an anonymous Chinese individual HX1, Huddleston et al. sequenced two effectively haploid human genomes from hydatidiform moles CHM1 and CHM13 that hence lack allelic variations. Haploid genomes facilitate contig assembly and structural variant detection compared with diploid genomes, and we considered the CHM1 and CHM13 sets the most reliable truth sets available to our knowledge at the time of testing.
We combined the CHM1 and CHM13 sets to produce a diploid truth set, which contained 66.5% more calls than HX1. We believe this difference is mainly caused by the difficulty in detecting structural variants in a diploid genome, where Huddleston et al. showed that they were unable to recover the majority of their heterozygous calls when using an effectively diploid version of CHM1 and CHM13.
CHM1 and CHM13 Illumina reads were sampled to create three different sets of 20x, 40x, and 80x coverages, while the reads available for HX1 provided coverage of 75x. We note that our benchmarking method does not evaluate alternate but equivalent variant representations and that the truth set calls may not always be precise. We, therefore, used an error margin of 50 base pairs when comparing ASVD and Manta calls with structural variants in each truth set (see also special notes for further details regarding benchmarks and data preparation).
Table 1: Benchmark of ASVD and Manta on artificial diploid WGS reads at varying coverage, obtained by sampling form a mix of CHM1 and CHM13 reads in addition to a HX1 comparison. A SV was considered a true positive, if the call was within 50 bp of the truth.
| Dataset | Model | Correct | Wrong | Precision | Sensitivity |
| 20x | ASVD | 3561 | 355 | 0.909 | 0.109 |
| Manta | 2992 | 327 | 0.901 | 0.092 | |
| 40x | ASVD | 4896 | 520 | 0.904 | 0.150 |
| Manta | 4835 | 754 | 0.865 | 0.148 | |
| 80x | ASVD | 4924 | 582 | 0.894 | 0.151 |
| Manta | 6566 | 1242 | 0.840 | 0.201 | |
| HX1 (75x) | ASVD | 3398 | 2007 | 0.629 | 0.174 |
| Manta | 4230 | 2326 | 0.645 | 0.216 |
The ASVD plugin and Manta perform comparably across the different sets. Both the ASVD plugin and Manta showed significantly more “false positives” in the HX1 set compared with the Huddleston et al. 20x - 80x sets. We believe this is an artifact of real SVs that are present, but not included in the HX1 truth set.
We assessed the performance separately for short and long structural variants for the typical scenario of 40x coverage Illumina whole genome sequencing. A detailed comparison of results for the Huddleston et al. 40x coverage set in table 2, where we only considered variants of minimum 50 base pairs and applied a cut-off between short and long structural variants at 100 base pairs.
Table 2: Benchmark of ASVD and Manta for short and long structural variants for the 40x coverage Illumina data set. A SV was considered a true positive, if the call was within 50 bp of the truth.
| Length | Model | Correct | Wrong | Precision | Sensitivity | |
| Deletions | 50 – 100 | ASVD | 934 | 87 | 0.915 | 0.179 |
| Manta | 1084 | 203 | 0.842 | 0.208 | ||
| 100 – 10000 | ASVD | 2170 | 219 | 0.908 | 0.322 | |
| Manta | 2113 | 264 | 0.889 | 0.314 | ||
| Insertions | 50 – 100 | ASVD | 734 | 94 | 0.886 | 0.099 |
| Manta | 836 | 134 | 0.862 | 0.112 | ||
| 100 – 10000 | ASVD | 1058 | 120 | 0.898 | 0.081 | |
| Manta | 802 | 153 | 0.840 | 0.061 |
We observed instances where the ASVD plugin and Manta made equivalent calls that appeared correct, but were not present or were represented differently in a truth set. This resulted in lower precision and sensitivity values overall for both tools that is likely to be the case.
These benchmarks suggest that ASVD and Manta have very comparable performances for short SVs and that ASVD performs slightly better than Manta for longer CVs.
(1) Sudmant, P.H., et al. (2015) An integrated map of structural variation in 2,504 human genomes. Nature, 526
(2) Chiang, C., et al. (2017) The impact of structural variation on human gene expression. Nat. Genet. 49(5):692-699.
(3) Chen, X,., et al. (2016) Manta: rapid detection of structural variants and indels for germline and cancer sequencing applications, Bioinformatics. 32(8):1220-2.
(4) Sedlazeck F J., et al. (2018) Accurate detection of complex structural variations using single-molecule sequencing. Nat. Methods. 15(6):461-468.
(5) Huddleston, J., et al. (2017) Discovery and genotyping of structural variation from long-read haploid genome sequence data. Genome Res. 27(5):677-685.
(6) Shi et al. (2016) Long-read sequencing and de novo assembly of a Chinese genome. Nat. Comm. 30(7):12065.
Human Gene Mutation Database (HGMD®) is the gold standard industry-leading resource for comprehensive coverage of published human inherited disease mutations. Unlike other mutation databases, HGMD mutations are backed by peer-reviewed publications where there is evidence of clinical impact.
You can also prioritize variants by disease concepts via the drop-down menu.
You now have the ability to browse HGMD phenotypes mapped to the UMLS (grouped into disease concepts, e.g., blood disorders) during the phenotype search. You can also filter results using these disease concepts in batch search mode (see above).
To get the most out of your HGMD subscription, please watch the video tutorials available at our Resources webpage.
Learn more about how ANNOVAR can be used with HGMD for variant annotation.
Watch a recorded webinar featuring ANNOVAR here.
View the complete Genome Trax™ statistics
Updated tracks have been released concurrent with the HGMD release for all HGMD-related tracks. Additional major tracks updated include TRANSFAC® release 2018.3, PROTEOME™ release 2018.3.
There are few meetings as important to the bioinformatics community as Intelligent Systems for Molecular Biology (ISMB), which is celebrating its 25th year at the upcoming event in Prague to be held July 21-25. Organized by the International Society for Computational Biology, ISMB is known for its wide range of presentations, from big-picture keynotes to its targeted “birds of a feather” discussions and much more. We love attending this conference as a way to connect with other bioinformatics geeks and hash out (bad pun fully intended) best practices for computational biology.
This year’s ISMB will be held in conjunction with the European Conference on Computational Biology. Organizers announced 14 communities of special interest (COSIs) that will be running themes throughout the event; examples include structural bioinformatics, visualization of biological data, and bioinformatics education.
Another COSI focuses on methods for understanding the impacts of genetic variation. In the VARI-COSI workshop taking place all day July 24, experts will offer a number of presentations and discussions on relevant topics. Our own Anika Joecker, Director of Clinical Partnering Bioinformatics, will give a talk entitled “The importance of using a most comprehensive knowledgebase for the identification of pathogenic variants in cancer and inherited diseases.” She’ll speak about HGMD as well as the QIAGEN Knowledge Base, which contains hundreds of thousands of manually curated pathogenic variants associated with oncology and inherited disease. The session will include real-world examples showing how scientists have used QIAGEN Clinical Insight Interpret and Ingenuity Variant Analysis to improve diagnosis and treatment for patients.
If you’re attending ISMB this year, enjoy!
The American College of Medical Genetics and Genomics Annual Meeting (ACMG 2017) takes place on March 21-25, in Phoenix, AZ.
Mark your calendar for March 23, where one of our partners has prepared a very interesting talk on rare and inherited diseases – don’t miss it.
Title: Using NGS Bioinformatics Solutions to Compare Exomes in Rare and Inherited Diseases and Identifying the Cause of Disease
Speaker: Shimul Chowdhury, PhD, DABMGG, CGMB, Rady Children's Institute for Genomic Medicine
Date and time: March 23, Thursday, 11:05 a.m. – 11:35 a.m.
Location: Theater 2
You’re also very welcome to stop by our booth #912 where our representatives will demonstrate our solutions.
We’re looking forward to seeing you!
Learn more about this meeting from their official website - Annual Clinical Genetics Meeting
