BOL: Related items

BioDownloader

Surabhi Chaudhary — Sat, 25 Feb 2017 17:52:33 -0600

BioDownloader is a program for downloading and/or updating files from ftp/http servers. The program has unique features that are specifically designed to deal with bioinformatics data files and servers:

optimized to work with vast amount of data and very large file sets (~ 10,000 - 100,000).
allows the selective retrieval of only the required files (file masks, ls-lR parsing, recursive search, updates)
has a built-in repository containing the settings for the most common bioinformatics download needs
built-in wizard for batch post-processing of downloaded files (archive extraction, file conversion, etc.)
capable of performing multiple download or update tasks simultaneously

BioDownloader has a built-in repository containing the settings for common bioinformatics file-synchronization needs, including the Protein Data Bank (PDB) and National Center for Biotechnology Information (NCBI) databases. It can post-process downloaded files, including archive extraction and file conversions.

http://dunbrack.fccc.edu/BioDownloader/

Address of the bookmark: http://dunbrack.fccc.edu/BioDownloader/

NCBI Magic-BLAST

Jit — Tue, 14 Aug 2018 18:11:11 -0500

Magic-BLAST is a tool for mapping large next-generation RNA or DNA sequencing runs against a whole genome or transcriptome. Each alignment optimizes a composite score, taking into account simultaneously the two reads of a pair, and in case of RNA-seq, locating the candidate introns and adding up the score of all exons. This is very different from other versions of BLAST, where each exon is scored as a separate hit and read-pairing is ignored.

Magic-BLAST incorporates within the NCBI BLAST code framework ideas developed in the NCBI Magic pipeline, in particular hit extensions by local walk and jump (http://www.ncbi.nlm.nih.gov/pubmed/26109056), and recursive clipping of mismatches near the edges of the reads, which avoids accumulating artefactual mismatches near splice sites and is needed to distinguish short indels from substitutions near the edges.

Address of the bookmark: https://ncbi.github.io/magicblast/

Blast on Docker, Google Cloud, Amazon Cloud

LEGE — Thu, 09 Jul 2020 02:57:11 -0500

As announced in a previous post, we offer a Docker version of NCBI BLAST+ that you can use locally or on the Google Cloud where we have pre-loaded BLAST databases. We are happy to announce that the same functionality is now available on the Amazon Cloud. In addition, we now offer 23 different BLAST databases on each cloud platform.

As mentioned before, working with BLAST+ in Docker and the cloud has several advantages:

Docker manages installation and maintenance of the BLAST programs and databases.
Docker makes it is easier to integrate BLAST with other tools in your pipelines.
NCBI BLAST databases are pre-loaded now on the both the Google Cloud and Amazon Cloud, providing fast access.

You can also use the BLAST+ Docker image on any Docker-enabled platform, such as another cloud platform or on your local computer.

See the BLAST+ in the Cloud and database information documentation to get started.

If you have any questions, please email us at blast-help@ncbi.nlm.nih.gov

Source:Dave Arndt

New Release of RefSeq !

Abhi — Tue, 16 Jul 2024 10:09:21 -0500

Check out RefSeq release 225, now available online and from the FTP site. You can access RefSeq data through NCBI Datasets.

What’s included in this release?

As of July 8, 2024, this full release incorporates genomic, transcript, and protein data containing:

448,507,905 records
334,845,613 proteins
63,542,774 RNAs
Sequences from 152,668 organisms

The release is provided in several directories as a complete dataset and also as divided by logical groupings.

Explore taxdump files !

Jit — Sat, 08 Feb 2020 04:44:55 -0600

This is an extract of taxdump-readme.txt to be found at 
ftp://ftp.ncbi.nih.gov/pub/taxonomy/

The content of the archive
--------------------------

It may look like this:

delnodes.dmp
division.dmp
gencode.dmp
merged.dmp
names.dmp
nodes.dmp
readme.txt

The readme.txt file gives a brief description of *.dmp files. These files
contain taxonomic information and are briefly described below. Each of the
files store one record in the single line that are delimited by "\t|\n"
(tab, vertical bar, and newline) characters. Each record consists of one 
or more fields delimited by "\t|\t" (tab, vertical bar, and tab) characters.
The brief description of field position and meaning for each file follows.

nodes.dmp
---------

This file represents taxonomy nodes. The description for each node includes 
the following fields:

	tax_id					-- node id in GenBank taxonomy database
 	parent tax_id				-- parent node id in GenBank taxonomy database
 	rank					-- rank of this node (superkingdom, kingdom, ...) 
 	embl code				-- locus-name prefix; not unique
 	division id				-- see division.dmp file
 	inherited div flag  (1 or 0)		-- 1 if node inherits division from parent
 	genetic code id				-- see gencode.dmp file
 	inherited GC  flag  (1 or 0)		-- 1 if node inherits genetic code from parent
 	mitochondrial genetic code id		-- see gencode.dmp file
 	inherited MGC flag  (1 or 0)		-- 1 if node inherits mitochondrial gencode from parent
 	GenBank hidden flag (1 or 0)            -- 1 if name is suppressed in GenBank entry lineage
 	hidden subtree root flag (1 or 0)       -- 1 if this subtree has no sequence data yet
 	comments				-- free-text comments and citations

names.dmp
---------
Taxonomy names file has these fields:

	tax_id					-- the id of node associated with this name
	name_txt				-- name itself
	unique name				-- the unique variant of this name if name not unique
	name class				-- (synonym, common name, ...)

division.dmp
------------
Divisions file has these fields:
	division id				-- taxonomy database division id
	division cde				-- GenBank division code (three characters)
	division name				-- e.g. BCT, PLN, VRT, MAM, PRI...
	comments

gencode.dmp
-----------
Genetic codes file:

	genetic code id				-- GenBank genetic code id
	abbreviation				-- genetic code name abbreviation
	name					-- genetic code name
	cde					-- translation table for this genetic code
	starts					-- start codons for this genetic code

delnodes.dmp
------------
Deleted nodes (nodes that existed but were deleted) file field:

	tax_id					-- deleted node id

merged.dmp
----------
Merged nodes file fields:

	old_tax_id                              -- id of nodes which has been merged
	new_tax_id                              -- id of nodes which is result of merging

PubMed opens for comment

Rahul Nayak — Thu, 24 Oct 2013 12:40:17 -0500

The informal conversations that researchers have at scientific meetings look set to move online, if a new initiative by the US National Center for Biotechnology Information (NCBI) has its way. On 22 October, the NCBI of Bethesda, Maryland, launched the pilot phase of a programme called PubMed Commons. This will allow users to comment on published abstracts on the PubMed website, which indexes some 22 million papers.

For now, only a select group of researchers and their invited guests can use the system. But the NCBI's director David Lipman, who helped to develop the programme, says that soon any PubMed author will be allowed to comment under his or her real name and anyone will be able to read the comments.

More @ http://www.nature.com/news/pubmed-opens-for-comment-1.14023

News source Nature.

Sequence Viewer: Download Transcripts, Exons and Proteins

Mon, 15 Sep 2014 17:30:36 -0500

How to download FASTA sequence for certain gene features while in the NCBI's Sequence Viewer. Sequence Viewer homepage: www.ncbi.nlm.nih.gov/projects/sviewer/ Sequence Viewer playlist: https://www.youtube.com/playlist?list=PL76D7EE6A6A8AC1C3

HistoneDB 2.0 – with variants

Anjana — Fri, 03 Jun 2016 05:06:20 -0500

This histone database can be used to explore the diversity of histone proteins and their sequence variants in many organisms. The resource was established to better understand how sequence variation may affect functional and structural features of nucleosomes. To get started, select a histone type to explore its variants.

More at http://www.ncbi.nlm.nih.gov/projects/HistoneDB2.0/index.fcgi/browse/

Address of the bookmark: http://www.ncbi.nlm.nih.gov/projects/HistoneDB2.0/index.fcgi/browse/

Download assemblies from NCBI

Bulbul — Mon, 15 May 2017 06:02:32 -0500

A new “Download assemblies” button is now available in the Assembly database. This makes it easy to download data for multiple genomes without having to write scripts.

For example, you can run a search in Assembly and use check boxes (see left side of screenshot below) to refine the set of genome assemblies of interest. Then, just open the “Download assemblies” menu, choose the source database (GenBank or RefSeq), choose the file type, and start the download. An archive file will be saved to your computer that can be expanded into a folder containing your selected genome data files.

More at https://ncbiinsights.ncbi.nlm.nih.gov/2017/05/08/genome-data-download-made-easy/

NCBI to assist in Virus Hunting Data Science Hackathon

BioStar — Thu, 15 Nov 2018 12:55:01 -0600

NCBI Hackathon are pleased to announce the second installment of the SoCal Bioinformatics Hackathon. From January 9-11, 2019, the NCBI will help run a bioinformatics hackathon in Southern California hosted by the Computational Sciences Research Center at San Diego State University!

NCBI Hackathon specifically looking for folks who have experience in computational virus hunting or adjacent fields to identify known, taxonomically-definable and novel viruses from a few hundred thousand metagenomic datasets that we’ll put on cloud infrastructure. This event is for researchers, including students and postdocs, who are already engaged in the use of bioinformatics data or in the development of pipelines for virological analyses from high-throughput experiments. If this describes you, please apply! The event is open to anyone selected for the hackathon and willing to travel to SDSU (see below).

https://ncbiinsights.ncbi.nlm.nih.gov/2018/11/09/ncbi-sdsu-virus-hunting-data-science-hackathon-january-2019/