BLAST+ 2.10.0 now available with improved composition-based statistics

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The BLAST+ 2.10.0 release is now available from our FTP site.  The new version offers the following improvements:

  • updated composition-based statistics for protein-protein (including translated BLAST) comparisons to provide stable results when you request fewer than the default number of results
  • an experimental Adaptive Composition Based Statistics option that increases the likelihood of finding novel results.  To enable this option set the environment variable ADAPTIVE_CBS to 1.  We welcome your feedback on this new option.

See the release notes for details on more  improvements and bug fixes with this release.

The new version fully supports the version 5 (v5) databases with built in taxonomy and other improvements. For more information on v5 databases (download), see the previous NCBI Insights article and the recording of our webinar.  If you are still using the older version 4 (v4) databases, we recommend you begin using the v5 version as soon as possible.  We will discontinue updates to the older v4 databases in early 2020.

Genome Workbench is now in the cloud!

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If you’re interested in visualizing and analyzing genomic data, then you’ll want to check out a new way to run Genome Workbench: in the cloud! Genome Workbench is a desktop application (both Windows and Mac) that lets you analyze genomic data in one place. You can run tools such as BLAST and create views such as multiple sequence alignments, and much more. You can run Genome Workbench on a cloud environment from your local desktop computer. This manual will show you how.

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There are many advantages to using Genome Workbench in the cloud:

  • You can easily compare your data to the complete GenBank and RefSeq datasets without needing to download them
  • You can run BLAST searches against standard databases or any custom databases you’ve assembled in the cloud
  • All of the data (e.g. FASTA, BAM, GFF files) remain in the cloud with no need for local copies
  • You won’t pay egress fees for downloading data

Give it a try and let us know how it goes!

Feature propagation in BankIt: easily annotate many sequences at once for GenBank submission

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Do you need a quick way to annotate features on a similar set of sequences for your GenBank submission? You can now submit sequences from the same region or gene in an alignment format in BankIt and use the new ‘Feature propagation option’ (Figure 1) to apply features from a single sequence to other aligned sequences. You simply annotate one sequence and then copy that annotation across all the sequences in your submission.

Here’s how you can propagate features in three easy steps:

  1. Provide nucleotide sequences in an alignment format.
  2. Select a sequence and annotate it.
  3. Propagate the features and edit results.

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New download files and FTP directories for genome assemblies

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You can now download new file types for species recently annotated by the NCBI Eukaryotic Genome Annotation Pipeline from the Assembly web pages and from the genomes/refseq FTP area. The new files types include alignments of annotated transcripts to the assembly in BAM format, all models predicted by Gnomon, and — for species that have been annotated multiple times —  files characterizing the feature-by-feature differences between the current and the previous annotation.

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Coming Soon: A New NIH Manuscript Submission (NIHMS) System!

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Reflecting the National Library of Medicine’s (NLM) ongoing commitment to public access support at the National Institutes of Health (NIH) and beyond, we are pleased to announce that a new NIHMS system will be released in early 2020. This new system aims to streamline the submission process, ensure the continued quality of manuscripts made publicly accessible, and give authors and investigators more transparent options for avoiding processing delays.

Those familiar with the current NIHMS system will find the basic steps of submitting, reviewing, and approving manuscripts for inclusion in PMC unchanged in the new system. They will see an updated user interface that simplifies the login process for returning users; provides contextual help throughout; and offers user-friendly options for importing article metadata, requesting corrections, and taking over the Reviewer role for stalled submissions. Details of these updates and more are available in this video:

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December 11 Webinar: Running the NCBI Prokaryotic Genome Annotation Pipeline (PGAP) on your own data

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On Wednesday, December 11, 2019 at 12 PM, NCBI staff will present a webinar that will show you how to use NCBI’s PGAP (https://github.com/ncbi/pgap) on your own data to predict genes on bacterial and archaeal genomes using the same inputs and applications used inside NCBI. You can run PGAP your own machine, a compute farm, or in the Cloud. Plus, you can now submit genome sequences annotated by your copy of PGAP to GenBank.  Attend the webinar to learn more!

  • Date and time: Wed, Dec 11, 2019 12:00 PM – 12:45 PM EDT
  • Register

After registering, you will receive a confirmation email with information about attending the webinar. A few days after the live presentation, you can view the recording on the NCBI YouTube channel. You can learn about future webinars on the Webinars and Courses page.

December 4 Webinar: Human population genetic variation data at NCBI

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On Wednesday, December 4, 2019 at 12 PM, NCBI staff will present a webinar on the population variation datasets at NCBI such as 1000 Genomes, ExAC, GnomAD, and TopMed that are currently included on dbSNP records. You will learn how to find the data, and how you can used this information to interpret and prioritize variants for further study. You will also see a preview a new initiative, the dbGaP Allele Frequency Aggregator (ALFA), that is based on more than 150,000 subjects in 60 dbGaP studies.

  • Date and time: Wed, Dec 4, 2019 12:00 PM – 12:45 PM EDT
  • Register

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New release of the Prokaryotic Genome Annotation Pipeline with updated tRNAscan and protein models

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A new version of the Prokaryotic Genome Annotation Pipeline (PGAP) is now available on GitHub. This release uses a new and improved version of tRNAscan (tRNAscan-SE:2.0.4) and includes our most up-to-date Hidden Markov Model and BlastRule collections for naming proteins.

Remember that you can submit the results of PGAP to GenBank. Or, if you are still improving the assembly and your genome doesn’t pass the pre-annotation validation, you can use the –ignore-all-errors mode to get a preliminary annotation.

See our previous post and our documentation for details on how to set up and run PGAP yourself.

Try PGAP and let us know how you like it!