BOL: Related items

Alignment-free sequence comparison tools available for next-generation sequencing data analysis

Abhimanyu Singh — Tue, 07 Nov 2017 05:33:33 -0600

kallisto

Transcript abundance quantification from RNA-seq data (uses pseudoalignment for rapid determination of read compatibility with targets)

Software (C++)

https://pachterlab.github.io/kallisto/

Sailfish

Estimation of isoform abundances from reference sequences and RNA-seq data (k-mer based)

Software (C++)

http://www.cs.cmu.edu/~ckingsf/software/sailfish/

Salmon

Quantification of the expression of transcripts using RNA-seq data (uses k-mers)

https://combine-lab.github.io/salmon/

RNA-Skim

RNA-seq quantification at transcript-level (partitions the transcriptome into disjoint transcript clusters; uses sig-mers, a special type of k-mers)

Software (C++)

http://www.csbio.unc.edu/rs/

Variant calling

ChimeRScope

Fusion transcript prediction using gene k-mers profiles of the RNA-seq paired-end reads

Software (Java)

https://github.com/ChimeRScope/ChimeRScope/wiki

FastGT

Genotyping of known SNV/SNP variants directly from raw NGS sequence reads by counting unique k-mers

Software (C)

https://github.com/bioinfo-ut/GenomeTester4/

Phy-Mer

Reference-independent mitochondrial haplogroup classifier from NGS data (k-mer based)

Software (Python)

https://github.com/danielnavarrogomez/phy-mer

LAVA

Genotyping of known SNPs (dbSNP and Affymetrix's Genome-Wide Human SNP Array) from raw NGS reads (k-mer based)

Software (C)

http://lava.csail.mit.edu/

MICADo

Detection of mutations in targeted third-generation NGS data (can distinguish patients’ specific mutations; algorithm uses k-mers and is based on colored de Bruijn graphs)

Software (Python)

http://github.com/cbib/MICADo

General mapper

Minimap

Lightweight and fast read mapper and read overlap detector (uses the concept of “minimazers”, a special type of k-mers)

Software (C)

https://github.com/lh3/minimap

Assembly

De novo genome assembly

MHAP

Produces highly continuous assembly (fully resolved chromosome arms) from third-generation long and noisy reads (10 kbp) using a dimensionality reduction technique MinHash

Software (Java)

https://github.com/marbl/MHAP

Miniasm

Assembler of long noisy reads (SMRT, ONT) using the Overlap-Layout Consensus (OLC) approach without the necessity of an error correction stage (uses minimap)

Software (C)

https://github.com/lh3/miniasm

LINKS

Scaffolding genome assembly with error-containing long sequence (e.g., ONT or PacBio reads, draft genomes)

Software (Perl)

https://github.com/warrenlr/LINKS/

Read clustering

afcluster

Clustering of reads from different genes and different species based on k-mer counts

Software (C++)

https://github.com/luscinius/afcluster

QCluster

Clustering of reads with alignment-free measures (k-mer based) and quality values

Software (C++)

http://www.dei.unipd.it/~ciompin/main/qcluster.html

Reads error correction

Lighter

Correction of sequencing errors in raw, whole genome sequencing reads (k-mer based)

Software (C++)

https://github.com/mourisl/Lighter

QuorUM

Error corrector for Illumina reads using k-mers

Software (C++)

https://github.com/gmarcais/Quorum

Trowel

Software (C++)

https://sourceforge.net/projects/trowel-ec/

Metagenomics

Assembly-free phylogenomics

AAF

Phylogeny reconstruction directly from unassembled raw sequence data from whole genome sequencing projects; provides bootstrap support to assess uncertainty in the tree topology (k-mer based)

Software (Python)

https://github.com/fanhuan/AAF

kSNP v3

Reference-free SNP identification and estimation of phylogenetic trees using SNPs (based on k-mer analysis)

Software (C)

https://sourceforge.net/projects/ksnp/files/

NGS-MC

Phylogeny of species based on NGS reads using alignment-free sequence dissimilarity measures d2* and d2 S under different Markov chain models (using k-words)

R package

http://www-rcf.usc.edu/~fsun/Programs/NGS-MC/NGS-MC.html

Species identification/taxonomic profiling

CLARK

Taxonomic classification of metagenomic reads to known bacterial genomes using k-mer search and LCA assignment

Software (C++)

http://clark.cs.ucr.edu/

FOCUS

Reports organisms present in metagenomic samples and profiles their abundances (uses composition-based approach and non-negative least squares for prediction)

Web service Software (Python)

http://edwards.sdsu.edu/FOCUS/

GSM

Estimation of abundances of microbial genomes in metagenomic samples (k-mer based)

Software (Go)

https://github.com/pdtrang/GSM

Mash

Species identification using assembled or unassembled Illumina, PacBio, and ONT data (based on MinHash dimensionality-reduction technique)

Software (C++)

https://github.com/marbl/mash

Kraken

Taxonomic assignment in metagenome analysis by exact k-mer search; LCA assignment of short reads based on a comprehensive sequence database

Software (C++)

https://ccb.jhu.edu/software/kraken/

LMAT

Assignment of taxonomic labels to reads by k-mers searches in precomputed database

Software (C++/Python)

https://sourceforge.net/projects/lmat/

stringMLST

k-mer-based tool for MLST directly from the genome sequencing reads

Software (Python)

http://jordan.biology.gatech.edu/page/software/stringMLST

Taxonomer

k-mer-based ultrafast metagenomics tool for assigning taxonomy to sequencing reads from clinical and environmental samples

Web service

http://taxonomer.iobio.io/

Other

d2-tools

Word-based (k-tuple) comparison (pairwise dissimilarity matrix using d2S measure) of metatranscriptomic samples from NGS reads

Software (Python/R)

https://code.google.com/p/d2-tools/

VirHostMatcher

Prediction of hosts from metagenomic viral sequences based on ONF using various distance measures (e.g., d2)

Software (C++)

https://github.com/jessieren/VirHostMatcher

MetaFast

Statistics calculation of metagenome sequences and the distances between them based on assembly using de Bruijn graphs and Bray–Curtis dissimilarity measure

Software (Java)

https://github.com/ctlab/metafast

iSeqQC: a tool for expression-based quality control in RNA sequencing

BioStar — Sun, 16 Feb 2020 08:47:17 -0600

iSeqQC, an expression-based QC tool that detects outliers either produced due to variable laboratory conditions or due to dissimilarity within a phenotypic group. iSeqQC implements various statistical approaches including unsupervised clustering, agglomerative hierarchical clustering and correlation coefficients to provide insight into outliers.

http://cancerwebpa.jefferson.edu/iSeqQC/

https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-020-3399-8

Address of the bookmark: https://github.com/gkumar09/iSeqQC

Cancer's origins revealed

Jitendra Narayan — Thu, 15 Aug 2013 13:06:56 -0500

Researchers have provided the first comprehensive compendium of mutational processes that drive tumour development. Together, these mutational processes explain most mutations found in 30 of the most common cancer types. This new understanding of cancer development could help to treat and prevent a wide-range of cancers.

More at >> http://www.sanger.ac.uk/about/press/2013/130814.html

How DNA is Packaged (Advanced)

Mon, 23 Sep 2013 18:08:34 -0500

Each chromosome consists of one continuous thread-like molecule of DNA coiled tightly around proteins, and contains a portion of the 6,400,000,000 basepairs (DNA building blocks) that make up your DNA. Originally created for DNA Interactive ( http://www.dnai.org ). TRANSCRIPT: In this animation we'll see the remarkable way our DNA is tightly packed up to fit into the nucleus of every cell. The process starts with assembly of a nucleosome, which is formed when eight separate histone protein subunits attach to the DNA molecule. The combined tight loop of DNA and protein is the nucleosome. Six nucleosomes are coiled together and these then stack on top of each other. The end result is a fiber of packed nucleosomes known as chromatin. This structure, is then looped and further packaged using other proteins (which are not shown here) to give the final "chromosomal" shapes. It is this remarkable multiple folding which allows six feet of DNA to fit into the nucleus of each cell in our body. And a typical cell nucleus is so small that ten thousand could fit on the tip of a needle. It is important to realize that chromosomes are not always present, they form only when cells are dividing. At other times, as we can see here at the end of cell division, our DNA becomes less highly organized.)

Nucl2Vec: Local alignment of DNA sequences using Distributed Vector Representation

Jit — Tue, 16 Mar 2021 05:45:44 -0500

We demonstrate a novel approach forlocal alignment of DNA reads with respect to reference genome.For this process we have used Skip-gram model for creatingencoding(Nucl2Vec) and k-nearest neighbor for the alignment.With our new approach we have reduced computation cost forlocal alignment , while achieving accuracy comparable to existingdefacto standard BWA-MEM tool.

https://prakharg24.github.io/papers/401851.full.pdf

Address of the bookmark: https://prakharg24.github.io/papers/401851.full.pdf

DNA Transcription (Advanced)

Thu, 29 Jan 2015 05:31:42 -0600

Transcription is the process by which the information in DNA is copied into messenger RNA (mRNA) for protein production. Originally created for DNA Interactive ( http://www.dnai.org ). TRANSCRIPT: The Central Dogma of Molecular Biology: "DNA makes RNA makes protein" Here the process begins. Transcription factors assemble at a specific promoter region along the DNA. The length of DNA following the promoter is a gene and it contains the recipe for a protein. A mediator protein complex arrives carrying the enzyme RNA polymerase. It manoeuvres the RNA polymerase into place... inserting it with the help of other factors between the strands of the DNA double helix. The assembled collection of all these factors is referred to as the transcription initiation complex... and now it is ready to be activated. The initiation complex requires contact with activator proteins, which bind to specific sequences of DNA known as enhancer regions. These regions may be thousands of base pairs distant from the start of the gene. Contact between the activator proteins and the initiation-complex releases the copying mechanism. The RNA polymerase unzips a small portion of the DNA helix exposing the bases on each strand. Only one of the strands is copied. It acts as a template for the synthesis of an RNA molecule which is assembled one sub-unit at a time by matching the DNA letter code on the template strand. The sub-units can be seen here entering the enzyme through its intake hole and they are joined together to form the long messenger RNA chain snaking out of the top.

DIAMOND

Jit — Thu, 27 Apr 2017 04:21:54 -0500

DIAMOND is a sequence aligner for protein and translated DNA searches and functions as a drop-in replacement for the NCBI BLAST software tools. It is suitable for protein-protein search as well as DNA-protein search on short reads and longer sequences including contigs and assemblies, providing a speedup of BLAST ranging up to x20,000.

More at file:///home/urbe/Downloads/diamond_manual.pdf

http://www.nature.com/nmeth/journal/v12/n1/full/nmeth.3176.html

Address of the bookmark: https://github.com/bbuchfink/diamond

DNA testing companies around the globe !

Jit — Thu, 13 Jul 2017 04:44:03 -0500

It was realized in the 1940s that DNA molecules are passed down through the generations of a family. In 1953 Watson and Crick elucidated the chemical structure of this molecule as a twisted ladder (a ‘helix’) made of two strands. DNA occurs in all the cells of our body, it is our blueprint! The strands of DNA contain information in the form of a code, which in turn determines our individual traits and characteristics. This code, the genetic code, is the order of four types of DNA building block. When the two strands of DNA separate, each building block (‘base’) accurately templates a corresponding base on the newly made strand of DNA so that information is not lost but is instead duplicated and preserved.

Testing for similarities between DNA (deoxyribonucleic acid) samples from two people allows family relationships to be established – or disproved – to an extraordinarily high degree of certainty. A common use for a DNA test is to establish if a man is the biological father of a child; this is known as a paternity test. However, there are other uses for the science of DNA testing (also called genotyping), these include forensic analysis of human DNA samples, and tracking relationships amongst domesticated animals.

The order in which the bases occur in DNA is referred to as the DNA sequence. Each person is unique and just as people differ in their fingerprints, they also have a unique and slightly different DNA sequence. Half of a person’s DNA is received from their mother, and half is received from the father. However, while fingerprints have no value for establishing family relationships, the minor variations in DNA sequence are extraordinarily useful for this purpose. All cells of our body contain DNA, skin cells from the lining of the cheek provide a simple and convenient source of material.

DNA is purified from these cells and the minor variations are read out as a type of bar-code by a machine. When the net DNA ‘barcodes’ from family members are lined up next to each other it becomes clear when a child is related to biological parents because half the stripes in the bar-code like signature will line up with those of the mother, and half will line up with those of the father. On the other hand, in the absence of a biological relationship, the DNA signatures from a child and from a potential parent are not found to have 50% in common. It may be appreciated that DNA testing is the most convenient and scientifically accurate method of determining relationships between people.

Following are the list of companies who qssist in DNA testing:

DNA testing companies

23andMe (admixture, adoption, deep ancestry, genealogy) (health and trait reports also available in some countries)
24 genetics (admixture, exome sequencing, health, paternity, pharmacogenetics, whole genome sequencing) A company catering for the Spanish market
African Ancestry (deep ancestry)
AfricanDNA (FTDNA affiliate) (admixture, deep ancestry, genealogy)
AncestrybyDNA (admixture, deep ancestry)
AncestryDNA, a subsidiary of Ancestry.com (admixture, adoption, genealogy)
Atlas Biomed (deep ancestry, diet, health and traits, sport) A test catering for the Russian market
BritainsDNA (formerly Ethnoancestry) (admixture, deep ancestry)
Centrillion Biosciences (aka TribeCode) (admixture, deep ancestry)
CymruDNAWales - see BritainsDNA
Dante Labs (exome sequencing, health, whole genome sequencing) A test aimed at the European market
DNA Ancestry and Family Origin (FTDNA affiliate in the Middle East) (admixture, adoption, deep ancestry, full mtDNA sequencing, genealogy)
DNA Consultants (admixture, deep ancestry)
DNA Tribes (admixture)
DNA Worldwide (formerly a FTDNA partner. See also Living DNA)
Ethnoancestry - see BritainsDNA
Family Tree DNA (admixture, adoption, deep ancestry, full mtDNA sequencing, genealogy, Y chromosome sequencing)
Full Genomes Corporation (whole genome sequencing, Y-chromosome sequencing)
Gene by Gene - the parent company of Family Tree DNA which now incorporates the companies previously known as DNA Traits, DNA DTC and DNA Findings (research, health, exome sequencing, whole genome sequencing)
Genebase (deep ancestry, genealogy)
GenoTek (admixture, genealogy, diet and fitness, family planning, health, talents and sports) A company catering for the Russian market
Genographic Project (admixture, deep ancestry)
Genos Research Inc (DTC whole exome sequencing; consumer focused healthcare big data spin out from Complete Genomics; Note: no genetic genealogy focus or tools)
Guardiome (admixture, whole genome sequencing and interpretation)
Helix (exome sequencing) US supplier of the Genographic Project Geno 2.0 Next Generation test
iGENEA (FTDNA affiliate) (admixture, deep ancestry, genealogy)
IrelandsDNA - See BritainsDNA (formerly Ethnoancestry)
MyDNA Global - a new name for BritainsDNA
Living DNA (admixture, deep ancestry) See also DNA Worldwide
MyHeritage DNA (admixture, genealogy)
Oxford Ancestors (deep ancestry)
Roots for Real (admixture, deep ancestry)
ScotlandsDNA - (formerly Ethnoancestry) (admixture, deep ancestry)
Sorenson Genomics (laboratory services)
Sure Genomics (whole genome sequencing and interpretation)
TribeCode See Centrillion Biosciences
Veritas Genetics (whole genome sequencing and interpretation)
Xcode (Diet and Fitness, Precision medicine, Genotyping, Sequencing, Interpretation)
YorkshiresDNA - See BritainsDNA (formerly Ethnoancestry)
WeGene (admixture, deep ancestry, health, sports, traits) A test tailored for the East Asian market
YSEQ (custom Y-SNPs, Y-STRs, SNP panels, whole genome sequencing)

TAREAN: A computational tool for identification and characterization of satellite DNA from unassembled short reads

Surabhi Chaudhary — Tue, 15 May 2018 02:53:11 -0500

TAndem REpeat ANalyzer -TAREAN – is a computational pipeline for unsupervised identification of satellite repeats from unassembled sequence reads. The pipeline uses low-pass whole genome sequence reads and performs their graph-based clustering. Resulting clusters, representing all types of repeats, are then examined for the presence of circular structures and putative satellite repeats are reported.

How to use TAREAN:

Install a local instance of the pipeline using its source code available from bitbucket repository.
Use public Galaxy-based server at https://repeatexplorer-elixir.cerit-sc.cz/. The server is provided in frame of the Elixir CZ project and is maintained by CESNET and CERIT-SC. Simple registration is required to use this service.

Development of TAREAN was supported by ELIXIR CZ research infrastructure project (MEYS Grant No: LM2015047).

References

Novak, P., Avila Robledillo, L., Koblizkova, A., Vrbova, I., Neumann, P., Macas, J. (2017) – TAREAN: a computational tool for identification and characterization of satellite DNA from unassembled short reads. Nucleic Acids Res., doi:10.1093/nar/gkx257

Address of the bookmark: https://bitbucket.org/petrnovak/repex_tarean

RopeBWT2: Incremental construction of FM-index for DNA sequences

Rahul Nayak — Thu, 25 Oct 2018 04:48:54 -0500

RopeBWT2 is an tool for constructing the FM-index for a collection of DNA sequences. It works by incrementally inserting one or multiple sequences into an existing pseudo-BWT position by position, starting from the end of the sequences. This algorithm can be largely considered a mixture of BCR and dynamic FM-index. Nonetheless, ropeBWT2 is unique in that it may implicitlysort the input into reverse lexicographical order (RLO) or reverse-complement lexicographical order (RCLO) while building the index.

Address of the bookmark: https://github.com/lh3/ropebwt2