BOL: Related items

The Tree That Learned to Read Genomes

BioStar — Fri, 11 Sep 2026 00:51:02 -0500

Imagine trying to reconstruct a family tree when many family photographs are missing, some names are unclear, and different relatives remember the past differently. This is similar to the challenge scientists face when trying to understand how organisms are related. Their family records are genomes, and the family tree is a phylogenetic tree. With modern sequencing technologies, scientists now have access to thousands of genomes, but comparing them can be difficult, especially when genomes are incomplete or poorly annotated.

A recent study by Webster and Chapman introduces Buscogeny (https://github.com/Jwebster89/Buscogeny), an open-source bioinformatics pipeline designed to make this process easier. The tool uses BUSCO (Benchmarking Universal Single-Copy Orthologs), which identifies conserved genes that are expected to occur as single copies in particular groups of organisms. These genes act like evolutionary landmarks, allowing researchers to compare genomes and investigate their relationships.

Buscogeny brings several steps of phylogenomic analysis into one workflow. It identifies BUSCO genes, extracts and aligns their sequences, removes unreliable regions, combines information from multiple genes, and uses the resulting data to construct a phylogenetic tree. It also provides quality-control information, helping researchers identify genomes that may be too incomplete for reliable analysis.

The authors demonstrate the usefulness of Buscogeny with bacterial and fungal genomes, including Alternaria. This is particularly valuable because fungal genomes can vary greatly in quality and annotation. Ultimately, Buscogeny helps transform massive amounts of genomic data into an understandable evolutionary story. Each DNA sequence becomes a clue, each conserved gene becomes a landmark, and together these clues reveal a picture of how life is connected.

More at https://link.springer.com/article/10.1007/s10123-025-00752-6?

Kmer: a suite of tools for DNA sequence analysis

BioStar — Wed, 18 Aug 2021 00:02:54 -0500

More at https://help.rc.ufl.edu/doc/Kmer

This also includes:

A2Amapper: ATAC, Assembly to Assembly Comparision tool:
- Comparative mapping between two genome assemblies (same species), or between two different genomes (cross species).

Sim4db:
- Spliced alignment of cDNA and genomic sequences, from the same (sim4) or related (sim4cc) species. Optimized for high-throughput batched alignment.

LEAFF:
- LEAFF (ahem, Let's Extract Anything From Fasta) is a utility program for working with multi-fasta files. In addition to providing random access to the base level, it includes several analysis functions.

Meryl:
- An out-of-core k-mer counter. The amount of sequence that can be processed for any size k depends only on the amount of free disk space.

Address of the bookmark: https://help.rc.ufl.edu/doc/Kmer

kebabs: package provides functionality for kernel based analysis of biological sequences via Support Vector Machine (SVM) based methods

Rahul Nayak — Fri, 04 Mar 2022 00:14:11 -0600

The kebabs package provides functionality for kernel based analysis of biological sequences via Support Vector Machine (SVM) based methods. Biological sequences include DNA, RNA, and amino acid (AA) sequences. Sequence kernels define similarity measures between sequences. The package implements some of the most important kernels for sequence analysis in a very flexible and efficient way and extends the standard position-independent functionality of these kernels in a novel way to take the position of patterns in the sequences into account for the similarity measure.

http://www.bioinf.jku.at/software/kebabs/

http://bioconductor.org/packages/release/bioc/vignettes/kebabs/inst/doc/kebabs.pdf

Address of the bookmark: http://www.bioinf.jku.at/software/kebabs/

SCUBAT: Scaffolding Contigs Using Blat And Transcripts

Rahul Nayak — Tue, 13 Mar 2018 06:52:24 -0500

SCUBAT (Scaffolding Contigs Using BLAT And Transcripts) uses any set of transcripts to identify cases where a transcript is split over multiple genome fragments and attempts to use this information to scaffold the genome.

Address of the bookmark: https://github.com/elswob/SCUBAT

Converting FASTQ to FASTA

Neel — Fri, 12 Jan 2018 03:49:09 -0600

There are several ways you can convert fastq to fasta sequences. Some methods are listed below.

Using SED

sed can be used to selectively print the desired lines from a file, so if you print the first and 2rd line of every 4 lines, you get the sequence header and sequence needed for fasta format.

sed -n '1~4s/^@/>/p;2~4p' INFILE.fastq > OUTFILE.fasta

Using PASTE

You can linerize every 4 lines in a tabular format and print first and second field using paste

cat INFILE.fastq | paste - - - - |cut -f 1, 2| sed 's/@/>/'g | tr -s "/t" "/n" > OUTFILE.fasta

EMBOSS:seqret

Standard script that can be used for many purposes. One such use is fastq-fasta conversion

seqret -sequence reads.fastq -outseq reads.fasta

awk can be used for conversion as follows:

Using AWK

cat infile.fq | awk '{if(NR%4==1) {printf(">%s\n",substr($0,2));} else if(NR%4==2) print;}' > file.fa

FASTX-toolkit

fastq_to_fasta is available in the FASTX-toolkit that scales really well with the huge datasets

fastq_to_fasta -h
usage: fastq_to_fasta [-h] [-r] [-n] [-v] [-z] [-i INFILE] [-o OUTFILE]
# Remember to use -Q33 for illumina reads!
version 0.0.6
       [-h]         = This helpful help screen.
       [-r]         = Rename sequence identifiers to numbers.
       [-n]         = keep sequences with unknown (N) nucleotides.
                   Default is to discard such sequences.
       [-v]         = Verbose - report number of sequences.
                   If [-o] is specified,  report will be printed to STDOUT.
                   If [-o] is not specified (and output goes to STDOUT),
                   report will be printed to STDERR.
       [-z]         = Compress output with GZIP.
       [-i INFILE]  = FASTA/Q input file. default is STDIN.
       [-o OUTFILE] = FASTA output file. default is STDOUT.

Bioawk

Another option to convert fastq to fasta format using bioawk

bioawk -c fastx '{print ">"$name"\n"$seq}' input.fastq > output.fasta

Seqtk

From the same developer, there is another option using a tool called seqtk

seqtk seq -a input.fastq > output.fasta

Note that you can use either compressed or uncompressed files for this tool

New born babies get ready to know their whole genome soon!!!

Rahul Agarwal — Thu, 05 Sep 2013 07:24:02 -0500

USA launch a pilot projects to examine medical information of newborn baby, which are being funded by the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) and the National Human Genome Research Institute (NHGRI), both parts of the National Institutes of Health.

Awards of $5 million to four grantees have been made in fiscal year 2013 under the Genomic Sequencing and Newborn Screening Disorders research program. The program will be funded at $25 million over five years, as funds are made available.

"Hundreds of US babies will be pioneers in genomic medicine through a US$25-million programme to sequence their genomes soon after they are born."

Source:

http://blogs.nature.com/news/2013/09/scientists-to-sequence-hundreds-of-newborns-genomes.html

http://www.genome.gov/27554919

GOLD:Genomes Online Database

Jit — Wed, 26 Jul 2017 07:49:29 -0500

GOLD:Genomes Online Database, is a World Wide Web resource for comprehensive access to information regarding genome and metagenome sequencing projects, and their associated metadata, around the world.

https://gold.jgi.doe.gov/

Address of the bookmark: https://gold.jgi.doe.gov/

coursera genome assembly tutorial

Jit — Sat, 25 Nov 2017 08:57:25 -0600

Solutions to Coursera Genome Sequencing (Bioinformatics II)

Address of the bookmark: https://github.com/iansealy/coursera-assembly

Bandage: interactive visualization of de novo genome assemblies

Shruti Paniwala — Mon, 04 Dec 2017 10:09:37 -0600

Bandage (a Bioinformatics Application for Navigating De novo Assembly Graphs Easily) is a tool for visualizing assembly graphs with connections. Users can zoom in to specific areas of the graph and interact with it by moving nodes, adding labels, changing colors and extracting sequences. BLAST searches can be performed within the Bandage graphical user interface and the hits are displayed as highlights in the graph. By displaying connections between contigs, Bandage presents new possibilities for analyzing de novo assemblies that are not possible through investigation of contigs alone.

Availability and implementation: Source code and binaries are freely available at https://github.com/rrwick/Bandage. Bandage is implemented in C++ and supported on Linux, OS X and Windows. A full feature list and screenshots are available at http://rrwick.github.io/Bandage.

Address of the bookmark: http://rrwick.github.io/Bandage/

Mugsy: multiple whole genome alignment tool

Jit — Fri, 08 Dec 2017 17:41:14 -0600

Mugsy is a multiple whole genome aligner. Mugsy uses Nucmer for pairwise alignment, a custom graph based segmentation procedure for identifying collinear regions, and the segment-based progressive multiple alignment strategy from Seqan::TCoffee. Mugsy accepts draft genomes in the form of multi-FASTA files and does not require a reference genome.

To cite Mugsy, use:

Angiuoli SV and Salzberg SL. Mugsy: Fast multiple alignment of closely related whole genomes.Bioinformatics 2011 27(3):334-4

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