BOL: Related items

BLAST+ 2.10.0 released

Jit — Wed, 18 Dec 2019 20:44:11 -0600

The BLAST+ 2.10.0 release is now available from at 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.

BLAST+ is also available in docker, please read more for details.

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.

BLAST+ Team

NCBI BLAST have added new columns to the Descriptions

Neel — Tue, 01 Dec 2020 09:56:07 -0600

NCBI BLAST have added new columns to the Descriptions Table for web BLAST output. The new columns are Scientific Name, Common Name, Taxid, and Accession Length. Common Name and Accession Length are now part of the default display. You can click 'Select columns' or 'Manage columns' to add or remove columns from the display Your preferences will be saved for your next visit to BLAST, and when you download your results, whatever columns you have displayed will be saved. See the NCBI Insights post (https://go.usa.gov/x7fPE) for more details.

Cleaner BLAST Databases for More Accurate Results

LEGE — Tue, 23 Apr 2024 01:23:08 -0500

Do you use BLAST to identify a sequence or the evolutionary scope of a gene? That can be challenging if contaminated and misclassified sequences are in the BLAST databases and show up in your search results. To address this problem, we now use the NCBI quality assurance tools listed below to systematically remove these misleading sequences from the default nucleotide (nt) and protein (nr) BLAST databases.

Foreign Contamination Screen tool for genome cross-species screening (FCS-GX) detects contamination from foreign organisms in genomes and other sequences using the genome cross-species aligner (GX)
Average Nucleotide Identity (ANI) evaluates the taxonomic classification of prokaryotic genome assemblies. Sequences from genomes marked up as ‘unverified source organism’ are considered suspect and removed.

Ref https://ncbiinsights.ncbi.nlm.nih.gov/2024/04/22/cleaner-blast-databases-more-accurate-results/

NCBI PSI-BLAST Tutorial

Fri, 23 Aug 2013 02:25:02 -0500

http:--www.biotechnology.jhu.edu- Tutorial for PSI-BLAST, an extension of BLAST that uses matrix algebra. BLAST is a cornerstone bioinformatics tool at NCBI. BLAST is the Basic Local Alignment Search tool and will protein and DNA sequences that are related to a sequence that the user provides.

A fast package to parse BLAST

Jitendra Narayan — Tue, 10 Sep 2013 16:58:56 -0500

In current era, we are handling huge amount of genomics data, and analysing it to make some biological sense out of it. Large-scale sequence studies requiring BLAST-based analysis produce huge amounts of data to be parsed. There are several BLAST parsers are available, but they are often missing some important features, such as keeping all information from the raw BLAST output, allowing direct access to single results, and performing logical operations over them.

Massimiliano Orsini and Simone Carcangiu develope a new and fast fast package "BlaSTorage" to parse and store BLAST results. BlaSTorage shows comparable speed of more basic parser written in compiled languages as C++ and can be easily integrated into web applications or software pipelines.

Find more @ http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3571973/

http://biowiki.crs4.it/biowiki/MassimilianoOrsini

BLAST Ring Image Generator (BRIG)

Anjana — Fri, 30 Sep 2016 09:18:50 -0500

BRIG is a free cross-platform (Windows/Mac/Unix) application that can display circular comparisons between a large number of genomes, with a focus on handling genome assembly data. The application is available at: http://sourceforge.net/projects/brig

If you have any questions or comments, post them on one of the trackers on BRIG’s SourceForge page: http://sourceforge.net/tracker/?group_id=328245.

Features:

Images show similarity between a central reference sequence and other sequences as concentric rings.
BRIG will perform all BLAST comparisons and file parsing automatically via a simple GUI.
Contig boundaries and read coverage can be displayed for draft genomes; customized graphs and annotations can be displayed.
Using a user-defined set of genes as input, BRIG can display gene presence, absence, truncation or sequence variation in a set of complete genomes, draft genomes or even raw, unassembled sequence data.
BRIG also accepts SAM-formatted read-mapping files enabling genomic regions present in unassembled sequence data from multiple samples to be compared simultaneously

Address of the bookmark: http://brig.sourceforge.net/

Converting BLAST output into CSV

Poonam Mahapatra — Mon, 11 Dec 2017 04:17:58 -0600

Suppose we wanted to do something with all this BLAST output. Generally, that’s the case - you want to retrieve all matches, or do a reciprocal BLAST, or something.

As with most programs that run on UNIX, the text output is in some specific format. If the program is popular enough, there will be one or more parsers written for that format – these are just utilities written to help you retrieve whatever information you are interested in from the output.

Let’s conclude this tutorial by converting the BLAST output in out.txt into a spreadsheet format, using a Python script.

First, we need to get the script. We’ll do that using the ‘git’ program:

git clone https://github.com/ngs-docs/ngs-scripts.git /root/ngs-scripts

We’ll discuss ‘git’ more later; for now, just think of it as a way to get ahold of a particular set of files. In this case, we’ve placed the files in /root/ngs-scripts/, and you’re looking to run the script blast/blast-to-csv.py using Python:

python /root/ngs-scripts/blast/blast-to-csv.py out.txt

This outputs a spread-sheet like list of names and e-values. To save this to a file, do:

python /root/ngs-scripts/blast/blast-to-csv.py out.txt > ~out.csv

If you have Excel installed, try double clicking on it.

BLAST+ 2.11.0 release is now available on FTP site !

Jit — Sat, 14 Nov 2020 21:37:53 -0600

BLAST+ 2.11.0 release is now available from our FTP site. The main advance is the ability to provide usage reports to NCBI to help us improve BLAST. This information is limited to the name of the BLAST program, some basic database metadata, a few BLAST parameters, as well the number and total size of your queries. See the Privacy document for more details on the information we collect, how we will use it, and how you can opt-out of reporting.

Another new feature allows threading by query batch in rpsblast/rpstblastn. Enabling this option using -m t provides more efficient searching with large numbers of queries. See release notes for details on more improvements and bug fixes.

Useful Links
------------
NCBI Insights: https://ncbiinsights.ncbi.nlm.nih.gov/2020/11/12/blast-2-11-0/

BLAST FTP: https://go.usa.gov/x7QQ3
Privacy document: https://go.usa.gov/x7QQe
Release notes: https://go.usa.gov/x7Qnv

Basics of BLAST Programs !

BioStar — Fri, 26 Jul 2024 06:04:26 -0500

The Basic Local Alignment Search Tool (BLAST) is a powerful bioinformatics program used to compare an input sequence (such as DNA, RNA, or protein sequences) against a database of sequences to find regions of similarity. Developed by the National Center for Biotechnology Information (NCBI), BLAST is widely used for identifying species, finding functional and evolutionary relationships between sequences, and predicting the function of novel sequences.

Key Features of BLAST:
1. Sequence Comparison: BLAST searches for local alignments between the query sequence and sequences in a database. It identifies regions of similarity, which can help infer functional and evolutionary relationships.

2. Speed and Efficiency: BLAST uses heuristic algorithms, making it faster than exhaustive search methods, suitable for large-scale database searches.

3. Versatility: There are several versions of BLAST for different types of sequence comparisons:
- blastn: Compares a nucleotide query sequence against a nucleotide sequence database.
- blastp: Compares a protein query sequence against a protein sequence database.
- blastx: Compares a nucleotide query sequence translated in all reading frames against a protein sequence database.
- tblastn: Compares a protein query sequence against a nucleotide sequence database translated in all reading frames.
- tblastx: Compares the six-frame translations of a nucleotide query sequence against the six-frame translations of a nucleotide sequence database.

4. Scoring and E-value: BLAST results are scored based on the quality and length of the alignments. The E-value (expect value) indicates the number of alignments one can expect to find by chance, with lower E-values representing more significant matches.

5. Output Formats: BLAST provides results in various formats, including plain text, HTML, XML, and JSON, making it adaptable for different types of analyses and integrations with other tools.

Applications of BLAST:
- Genomic Research: Identifying genes, understanding genetic diversity, and mapping genome sequences.
- Protein Function Prediction: Inferring the function of unknown proteins by comparing them to known protein sequences.
- Evolutionary Studies: Exploring evolutionary relationships between organisms by comparing their genetic material.
- Medical Research: Identifying pathogens, understanding disease mechanisms, and developing treatments by comparing sequences of interest.

Overall, BLAST is an essential tool in bioinformatics, offering a reliable and efficient way to analyze and interpret biological sequence data.

Understanding BLASTn output format 6 !

Rahul Nayak — Wed, 27 Jun 2018 18:38:21 -0500

BLASTn output format 6

BLASTn maps DNA against DNA, for example gene sequences against a reference genome

blastn -query genes.ffn -subject genome.fna -outfmt 6

BLASTn tabular output format 6

Column headers:
qseqid sseqid pident length mismatch gapopen qstart qend sstart send evalue bitscore

1.	qseqid	query (e.g., gene) sequence id
2.	sseqid	subject (e.g., reference genome) sequence id
3.	pident	percentage of identical matches
4.	length	alignment length
5.	mismatch	number of mismatches
6.	gapopen	number of gap openings
7.	qstart	start of alignment in query
8.	qend	end of alignment in query
9.	sstart	start of alignment in subject
10.	send	end of alignment in subject
11.	evalue	expect value
12.	bitscore	bit score

Define your own output format

by adding the option -outfmt, as for example:

-outfmt "6 qseqid sseqid pident qlen length mismatch gapope evalue bitscore"

supported format specifiers are:
qseqid    Query Seq-id
qgi   Query GI
qacc    Query accesion
qaccver   Query accesion.version
qlen    Query sequence length
sseqid    Subject Seq-id
sallseqid All subject Seq-id(s), separated by a ';'
sgi       Subject GI
sallgi    All subject GIs
sacc      Subject accession
saccver   Subject accession.version
sallacc   All subject accessions
slen      Subject sequence length
qstart    Start of alignment in query
qend    End of alignment in query
sstart    Start of alignment in subject
send      End of alignment in subject
qseq      Aligned part of query sequence
sseq      Aligned part of subject sequence
evalue    Expect value
bitscore  Bit score
score   Raw score
length    Alignment length
pident    Percentage of identical matches
nident    Number of identical matches
mismatch  Number of mismatches
positive  Number of positive-scoring matches
gapopen   Number of gap openings
gaps      Total number of gaps
ppos      Percentage of positive-scoring matches
frames    Query and subject frames separated by a '/'
qframe    Query frame
sframe    Subject frame
btop      Blast traceback operations (BTOP)
staxids   Subject Taxonomy ID(s), separated by a ';'
sscinames Subject Scientific Name(s), separated by a ';'
scomnames Subject Common Name(s), separated by a ';'
sblastnames Subject Blast Name(s), separated by a ';'   (in alphabetical order)
sskingdoms  Subject Super Kingdom(s), separated by a ';'     (in alphabetical order)
stitle    Subject Title
salltitles  All Subject Title(s), separated by a '<>'
sstrand   Subject Strand
qcovs   Query Coverage Per Subject
qcovhsp   Query Coverage Per HSP

default values are:
-outfmt "6 qseqid sseqid pident length mismatch gapopen qstart qend sstart send evalue bitscore"