Interested in understanding how sequence data are submitted, processed, and made publicly available in GenBank and the Sequence Read Archive (SRA)? Announcing the GenBank and SRA Data Processing webpage!
Here you can learn about procedures that the National Center for Biotechnology Information (NCBI), part of the National Library of Medicine (NLM), uses for processing submitted data and public posting, as well as key definitions of data status. Continue reading “Announcing the GenBank and SRA Data Processing Webpage”→
Are you familiar with the well-known Framingham Heart Study, a multi-generation study of residents of Framingham, Massachusetts begun in 1948? Much of what is now known about the impact of genetics, lifestyle, and diet on cardiovascular health and disease has come from this research study. (See PMC4159698 for a historical perspective.) Did you know that data from this study and over 2,000 other studies that demonstrate the relationship between genetic and medical outcomes and other phenotypes are available from NCBI’s Database of Genotypes and Phenotypes (dbGaP)?
dbGaP was established in 2007 as a repository of human data from large scale studies. You can access data from more than 2.8 million study participants who have provided over 3.3 million molecular samples. You can retrieve patient-level phenotypic (e.g., demographic, clinical, exposure) data and molecular (e.g., called genotypes omics, sequence) data, and the results of association analyses from genome-scale case-control and longitudinal studies of heritable diseases.
What types of studies and data are available in dbGaP?
dbGaP contains a wide range of studies and types of data, all relating to human genetic and phenotypic measurements. Most dbGaP data are from NIH-funded research, but recently we have expanded to include non-NIH funded studies. An easy way to find dbGaP Studies, Phenotype and Molecular Datasets, Variables, Analyses and Documents is through the dbGaP Advanced Search (Figure 1). The interface allows you to filter results by different characteristics depending on the tab you choose.
Figure 1. The dbGaP Advanced Search interface. Tabs that appear at the top of the web interface allow you to select the studies, datasets, analyses, etc. of interest. Filters (facets) appear on the left (see inset). Click on filters to select values to find Links on the study summary pages provide direct access to data. Top panel: Studies tab and the corresponding filter categories. Bottom panel: Molecular data tab results with Study (Framingham SHARe), Markerset Source (Affymetrix) filters applied.
The first complete genome sequence of the current monkeypox virus (MPXV) outbreak (isolate name MPXV_USA_2022_MA001) is now available with accession ON563414 in GenBank, a public database of DNA sequences hosted by the National Center for Biotechnology Information (NCBI) at the National Library of Medicine (NLM).
Several cases of monkeypox have been identified in geographically widespread countries. Monkeypox is classified as a zoonotic disease where transmission of the virus is usually due to animal-human contact. Genetically, monkeypox viruses cluster into two groups: the Congo basin and the west African clade. This particular outbreak has been identified as due to a virus from the west African clade which is often associated with milder disease and, in this case, human-to-human spread is suspected. Continue reading “Monkeypox virus: Complete genome from the current outbreak now available in GenBank”→
One impetus for development of the dashboard is that unassembled SRA data cannot be processed through Pango tools, and many SARS-CoV-2 samples are only represented in SRA. The Pango nomenclature is being used by researchers and public health agencies worldwide to track the transmission and spread of SARS-CoV-2, including variants of concern. Thus, we developed a uniform approach to making variant calls from SRA records and assigning Pangolin lineages on the basis of these results. This means that submission groups do not have to go through the effort of creating assemblies. Continue reading “Introducing SARS-CoV-2 Variants Overview, NLM’s latest tool in the fight against COVID-19 “→
BLAST+ 2.13.0 includes several important new features including SRA BLAST programs, ARM Linux executables, and the ability to produce database metadata as well as some important improvements, and a few bug fixes. You can download the new BLAST release from the FTP site.
New features
SRA / WGS BLAST (blastn_vdb, tblastn_vdb)
Beginning with this release, the BLAST distribution now includes the SRA BLAST programs blastn_vdb and tblastn_vdb that can directly search SRA and WGS projects without the need to build a BLAST database. See the BLAST documentation on how to use these programs with WGS projects.
ARM Linux executables
This release also includes executables compiled under ARM Linux for the first time. Please let us know if you find any issues with ARM Linux programs.
Database metadata in JSON format
Starting with BLAST+ 2.13.0, the makeblastdb program generates an additional file with the file extension .njs for nucleotide databases or .pjs for protein databases. These files contain BLAST database metadata in JSON format. See the BLAST database metadata section in the BLAST User Manual for an example. This file can be easily read by many tools and makes the BLAST database more compliant with FAIR principles.
See the release notes for more details on improvements and bug fixes for the release.
Important reminder about usage reporting
As we announced previously, BLAST can report limited usage information back to NCBI. This information shows us whether BLAST+ is being used by the community, and therefore is worth being maintained and developed. It also allows us to focus our development efforts on the most used aspects of BLAST+. Please help us improve BLAST by allowing BLAST to share information about your search. The BLAST privacy statement provides details on the information collected, how it is used, and how to opt-out of reporting if you don’t want to participate.
The Trace Archive at NCBI will be retired as of June 17, 2022. You may continue to retrieve Trace Archive content by searching the Sequence Read Archive (SRA) using TI number, organism, or center name at the time of retirement.
Missed a few videos on YouTube? Here’s the latest from our channel.
Customize the MSA Viewer to Make Your Analysis Easier
We’re constantly improving the Multiple Sequence Alignment (MSA) Viewer. This video demonstrates several new and popular features, including the ability to change data columns, hide selected rows, analyze polymorphisms, and more.
Did you know that you can see epigenomic or other experimental data in NCBI’s Genome Data Viewer (GDV)?
You can easily add aligned study results from GEO, SRA, and dbGaP as data tracks to GDV browser view. Just go to the Tracks button on the toolbar and select the menu option to Configure Tracks. Navigate to the ‘Find Tracks’ tab on the pop-up Configure panel (Figure 1).
Figure 1. Go to the ‘Tracks’ menu on the browser toolbar and select ‘Configure Tracks’ option. This will launch a panel where you can add, configure, remove, and search for data tracks. Go to the ‘Find Tracks’ tab to search for tracks to add to your browser view. Note: spaces act as AND operators in the search, and wildcards are accepted.
In response to your requests for compact and faster-to-deliver data, NIH’s Sequence Read Archive (SRA) now offers a new data format – SRA Lite (Figure 1). SRA Lite supports reliable and faster data transfer, downloads, and analysis using current tools. SRA Lite replaces the submitted base quality score (BQS) with a simplified read quality score, reducing the average read size by ~60% for more efficient analysis and storage of large datasets. This format was designed to reflect improvements in next-generation sequencing that include increases in average read length and sequence coverage. Indeed, the data has improved enough that that removing some quality scores increase genotype accuracy (PMCID: PMC4439189).
Figure 1. FASTQ dumped from SRA Lite format and the SRA configuration dialog. The FASTQ has the quality score for each base set to 30 (‘?’ in the ASCII encoding). Select “Prefer SRA Lite files with simplified base Quality scores” in the SRA configuration dialog to use SRA Lite.Continue reading “The Sequence Read Archive slims down your data with SRA Lite”→
