BOL: Related items

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/

New Layout for BLAST ftp Database Site

Jit — Tue, 21 Jan 2020 11:57:11 -0600

As announced previously, the new default database version for BLAST+ is dbV5. To complete this transition, the ftp database site will be updated to support this change. We expect this change to happen around February 4^th, please adjust your scripts or procedures accordingly.

Here is a list of what is changing:

All databases at the root level will be dbV5.
The dbV5 file naming, “_v5” will be removed. Databases with no “_vX” descriptor will be dbV5.
dbV4 tarballs will be renamed with "_v4", files included in tarball will not be renamed.
dbV4 databases will be moved to a v4 subdirectory.
As of 1/13/20 the Cloud directory will be frozen with no more new entries.
The will be no more updates to dbV4 databases.
The FASTA directory will contain nr, nt, swissprot, and pdbaa files.

If you have any questions or concerns, please contact blast-help@ncbi.nlm.nih.gov

Chemical Elements of Bioinformatics

Rahul Agarwal — Tue, 03 Sep 2013 16:35:39 -0500

You must be familiar with periodic table and colour pattern, but this time you are going to amaze by new elements table by Eagle genomics. Just check it out and have fun :)

http://elements.eaglegenomics.com/

BLAST options, setting and defaults

Jit — Mon, 10 Dec 2018 08:29:37 -0600

BLAST stands for Basic Local Alignment Search Tool and was developed by Altschul et al. (1990) and significantly improved by Altschul et al. (1997). It is a very fast search algorithm that is used to separately search protein or DNA databases. BLAST is best used for sequence similarity searching, rather than for motif searching. For searches using a query sequence of fewer than twenty residues, PatMatch is the best choice. Another sequence alignment tool that may yield different results from BLAST, and may be useful for motif searching, is FASTA. To search nonplant datasets, try NCGR BLAST or NCBI BLAST.

A fairly complete on-line guide to BLAST searching can be found at the NCBI BLAST Help Manual. For a theoretical overview of BLAST, see the NCBI BLAST Course. Additional information can be found in the BLAST 2.0 Release Notes

	BLASTN	BLASTP	BLASTX	TBLASTN	TBLASTX	PSIBLAST
Gap opening penalty: cost to open a gap [integer]	default = 5	default = 11 limited values are supported	default = 11 limited values are supported	default = 11 limited values are supported	default = 11 limited values are supported	default = 5
Gap extension penalty: cost to extend a gap [integer]	default = 2	default = 1 a 0 in this field means to use the default	default = 1 a 0 in this field means to use the default	default = 1 a 0 in this field means to use the default	default = 1 a 0 in this field means to use the default	default = 2
Nucleic match: reward for a match in the BLAST portion of run [integer]	default = 1	n/a	n/a	n/a	n/a	default = 1
Nucleic mismatch: penalty for a mismatch in the blast portion of run [integer]	default = -3	n/a	n/a	n/a	n/a	default = -3
Expectation value: (E) [real]	default = 10.0	default = 10.0	default = 10.0	default = 10.0	default = 10.0	default = 10.0
Word size: the size of the initial word that must be matched between the database and the query sequence	default = 11	default = 3	default = 3	default = 3	default = 3	default = 11
Max scores: Number of one-line descriptions (V) [Integer]	default = 25	default = 25	default = 25	default = 25	default = 25	default = 25
Max alignments: number of alignments to show (B) [integer]	default = 15	default = 15	default = 15	default = 15	default = 15	default = 15
Query filter: filter applied to the query sequence	default = DUST	default = SEG	default = SEG	default = SEG	default = SEG	default = DUST
Query genetic code: genetic code to be used in BLASTX translation of the query	n/a	n/a	default = universal	default = universal	default = universal	n/a
Matrix: substitution matrix to be used for amino acid comparisons	no default	default = blosum62	default = blosum62	default = blosum62	default = blosum62	no default

Supported and Suggested Values for Gap Open and Extension in BLASTP, BLASTX, TBLASTN, and TBLASTX

Gaps Open	Gap Extension
10	1
10	2
11	1
8	2
9	2

Address of the bookmark: https://www.arabidopsis.org/Blast/BLASToptions.jsp

NCBIBLAST+ 2.14.1 now available

Neel — Wed, 30 Aug 2023 02:36:13 -0500

#NCBIBLAST+ 2.14.1 now available with improved documentation, faster and more reliable database downloads, and some bug fixes.

Check out the changes they made.

They added the cleanup-blastdb-volumes.py script to remove unused BLAST database volumes. Read the documentation here.

They also switched the protocol from ftp to https to access BLAST databases for increased performance and reliability when downloading data from the NCBI with the update_blastdb.pl script.

And fixed a few bugs related to downloading data from the NCBI, and mt_mode crashing blastn and blastx.

Check out the release notes.

Download BLAST+ 2.14.1

Questions or comments? Please write the BLAST help desk.

More info and download: https://blast.ncbi.nlm.nih.gov/doc/blast-news/2023-BLAST-News.html

Run miniasm assembler on nanopore reads !

Jit — Mon, 18 Dec 2017 04:07:50 -0600

Miniasm is a very fast OLC-based de novo assembler for noisy long reads. It takes all-vs-all read self-mappings (typically by minimap) as input and outputs an assembly graph in the GFA format. Different from mainstream assemblers, miniasm does not have a consensus step. It simply concatenates pieces of read sequences to generate the final unitig sequences. Thus the per-base error rate is similar to the raw input reads.

Find the detail of the reads repeats:

fq2fa ONT_A.fastq ONT_A.fasta

minimap2 -xava-ont ONT_A.fasta ONT_A.fasta -t10 -X > AONT.paf

awk '{if($1==$6){print}}' AONT.paf > AONTself.paf

awk '$5=="-"' AONTself.paf | awk '{print $1}'| sort|uniq > invertedrepeat.list

Generated a few palindrome and repeats plots (highlighting only repeats largest than 10, 20 and 30 kb)

minidot -f 5 -m 30000 AONTself.paf > AONTself30000.eps
sed 's/_template_pass_FAH31515//' AONTself30000.eps > AONTself30000final.eps

minidot -f 5 -m 20000 AONTself.paf > AONTself20000.eps
sed 's/_template_pass_FAH31515//' AONTself20000.eps > AONTself20000final.eps

minidot -f 5 -m 10000 AONTself.paf > AONTself10000.eps
sed 's/_template_pass_FAH31515//' AONTself10000.eps > AONTself10000final.eps

Assemble with miniasm:

miniasm -f ONT_A.fasta AONT.paf > AONT.gfa
grep '^S' AONT.gfa |awk '{print ">"$2"\n"$3}' > AONT_miniasm.fasta

minimap2 -xasm10 AONT_miniasm.fasta AONT_miniasm.fasta -t1 -X > AONT_miniasm.paf

awk '{if($1==$6){print}}' AONT_miniasm.paf > AONT_miniasm_self.paf

minidot -f 5 -m 10000 AONT_miniasm_self.paf > AONT_miniasm_self10000.eps

Njoy the assembly !

Stay Connected and Productive: Unlock the Power of Screen, Tmux, and Mosh for Bioinformatics

BioStar — Wed, 22 Jan 2025 00:29:52 -0600

If you are a bioinformatician, chances are you have spent hours running long, complex analyses on remote servers only to lose your session because of an unstable connection. Frustrating, isnt it? Fear not! With tools like screen, tmux, and mosh, you can safeguard your workflow and stay productive, no matter where you are.

Why Remote Session Management is a Must-Have

In bioinformatics, tasks like genome assembly, RNA-seq analyses, and phylogenetic computations often take hours or days. A dropped SSH connection can result in:

Lost Progress: Restarting a job from scratch wastes valuable time.
Workflow Interruptions: Disruptions can derail your focus and productivity.
Corrupted Data: Interrupted processes may lead to incomplete or corrupted outputs.

By integrating screen, tmux, or mosh into your workflow, you can avoid these setbacks and ensure a seamless experience.

Screen: The Classic Workhorse

Screen is a terminal multiplexer that comes pre-installed on most Linux systems. It allows you to manage multiple terminal sessions and reconnect to them even after being disconnected.

Getting Started with Screen:

Start a Session:

screen
Detach from a Session:
Press Ctrl+A, then D.
Reattach to a Session:

screen -r

Pro Tip: Enhance your screen experience with a customized .screenrc configuration file. Download one here: Get .screenrc.

Tmux: A Modern Alternative

Tmux takes everything great about screen and adds modern features, including better key bindings and intuitive session management. It\u2019s perfect for bioinformaticians who want more control over their workflow.

Getting Started with Tmux:

Start a Session:

tmux
Detach from a Session:
Press Ctrl+B, then D.
Reattach to a Session:

tmux attach

Customize Your Tmux Experience:
Use a .tmux.conf file to personalize your setup. Grab one here: Download .tmux.conf.

Mosh: The Mobile Shell for Unreliable Connections

SSH works well for stable networks, but it struggles in areas with spotty connectivity. Enter Mosh, the Mobile Shell. Designed for intermittent networks, Mosh keeps your session alive even when the connection drops temporarily.

Why Mosh is a Game-Changer:

No lag over high-latency networks.
Automatically reconnects when the network is restored.
Ideal for working on the go, from cafes to trains.

Getting Started with Mosh:

Install Mosh:

sudo apt install mosh # For Debian/Ubuntu
Connect to a Server:

mosh username@server

Learn more at mosh.org.

Why This Matters for Bioinformatics

Every bioinformatician knows the value of time and data integrity. Tools like screen, tmux, and mosh provide a lifeline when running long analyses, enabling you to:

Safeguard your work against disconnections.
Easily manage multiple workflows in parallel.
Stay productive, even in challenging environments.

Quickstart Cheat Sheet

Screen:

screen # Start a session Ctrl+A, D # Detach screen -r # Reattach
Tmux:

tmux # Start a session Ctrl+B, D # Detach tmux attach # Reattach
Mosh:

mosh username@server

Final Thoughts

As a bioinformatician, your time is too valuable to spend restarting analyses due to technical hiccups. With screen, tmux, and mosh in your toolkit, you can work smarter, protect your progress, and stay productive no matter where you are. Start using these tools today and transform the way you work with remote systems.

Let me know how these tools work for you, and don\u2019t forget to follow for more bioinformatics tips!

BlasR Mapping single molecule sequencing reads using Basic Local Alignment with Successive Refinement (BLASR): Theory and Application,

Jit — Wed, 23 May 2018 06:54:32 -0500

BLASR (Basic Local Alignment with Successive Refinement) for mapping Single Molecule Sequencing (SMS) reads that are thousands to tens of thousands of bases long with divergence between the read and genome dominated by insertion and deletion error.

Here is how I use the blasr to align PacBio reads to the contigs (target.fasta). The “target.fasta.sa” is the suffix array from “target.fasta” generated by sawriter.

blasr query.fa ./target.fasta -sa ./target.fasta.sa -bestn 40 -maxScore -500 -m 4 -nproc 24 -out target.m4 -maxLCPLength 15

the output format option “-m 4″ generate the alignment coordinate. Not fully documented, but I can explain that to you.

I use a 24 cores / 48G ram server for the alignment. It took about 2 to 3 hours aligning 3G PacBio Reads to 10^6 sequences of short read contigs with a mean 3.5kbp length.

Address of the bookmark: http://bix.ucsd.edu/projects/blasr/

Bioinformatics 101 - Running BLAST

Tue, 03 Sep 2013 14:59:50 -0500

How to format the database for BLAST, run the command, view the output file, and use BioPerl and Perl to parse the output. By David Francis, Ohio State University. Delivered live at the Tomato Disease Workshop 2010. For more information, please visit http://www.extension.org/pages/32521/bioinformatics-101-video.