BOL: Related items

LAMSA: fast split read alignment with long approximate matches

Jit — Tue, 15 May 2018 04:44:42 -0500

LAMSA (Long Approximate Matches-based Split Aligner) is a novel split alignment approach with faster speed and good ability of handling SV events. It is well-suited to align long reads (over thousands of base-pairs). LAMSA takes takes the advantage of the rareness of SVs to implement a specifically designed two-step strategy. That is, LAMSA initially splits the read into relatively long fragments and co-linearly align them to solve the small variations or sequencing errors, and mitigate the effect of repeats. The alignments of the fragments are then used for implementing a sparse dynamic programming (SDP)-based split alignment approach to handle the large or non-co-linear variants. We benchmarked LAMSA with simulated and real datasets having various read lengths and sequencing error rates, the results demonstrate that it is substantially faster than the state-of-the-art long read aligners; mean-while, it also has good ability to handle various categories of SVs. LAMSA is open source and free for non-commercial use. LAMSA is mainly designed by Bo Liu & Yan Gao and developed by Yan Gao in Center for Bioinformatics, Harbin Institute of Technology, China.

Address of the bookmark: https://github.com/hitbc/LAMSA

ChIPulate: A Python3 framework to simulate read counts in a ChIP-seq experiment

Abhimanyu Singh — Mon, 25 Mar 2019 12:46:47 -0500

ChIP-seq simulation pipeline, ChIPulate, we assess the impact of various biological and experimental sources of variation on several outcomes of a ChIP-seq experiment, viz., the recoverability of the TF binding motif, accuracy of TF-DNA binding detection, the sensitivity of inferred TF-DNA binding strength, and number of replicates needed to confidently infer binding strength.

Address of the bookmark: https://github.com/vishakad/chipulate

Metabuli 분리 improves metagenomic read classification

Abhi — Sat, 03 Jun 2023 20:15:04 -0500

Metabuli 분리 improves metagenomic read classification through metamers, DNA-AA k-mers, to be sensitive and specific, recovering 99% and 98% of DNA or AA classifiers.

Metabuli is metagenomic classifier that jointly analyze both DNA and amino acid (AA) sequences. DNA-based classifiers can make specific classifications, exploiting point mutations to distinguish close taxa. AA-based classifiers have higher sensitivity in detecting homology between query and reference sequences, leverageing higher conservation of AA sequences. Metabuli combines the information of both sequence types using a novel k-mer structure, metamer, to enable both specific and sensitive characterization of metagenomic samples. In addition, it can classify reads against a database of any size as long as it fits in the hard disk.

Address of the bookmark: https://github.com/steineggerlab/Metabuli

Sequencing Solutions to World Health

Rahul Agarwal — Thu, 29 Aug 2013 15:05:35 -0500

"New technology that quickly, easily and economically reveals the genomes of viruses and pathogens transforms public health and medicine."

Source: Life technologies

Address of the bookmark: http://www.lifetechnologies.com/global/en/home/communities-social/blog/blogs/sequencing-solutions-to-world-health.html?cid=social_blogseries_20130829_11098264

Comparison of Short Read De Novo Alignment Algorithms

Rahul Agarwal — Wed, 21 Aug 2013 07:56:01 -0500

Excellent article to introduce different sequencing methods along with tools for de novo assembly of sequencing reads and their relevant references.

Title: Comparison of Short Read De Novo Alignment Algorithms

Author: Nikhil Gopal

Address of the bookmark: http://biochem218.stanford.edu/Projects%202011/Gopal%202011.pdf

Latest paper on comparison of mapping tools

Rahul Agarwal — Tue, 03 Sep 2013 18:00:38 -0500

A. Hatem, D. Bozdag, A. E. Toland, U. V. Catalyurek "Benchmarking short sequence mapping tools" BMC Bioinformatics, 14(1):184, 2013.

http://bmi.osu.edu/hpc/software/benchmark/

http://bmi.osu.edu/hpc/software/pmap/pmap.html

Other similiar papers:

http://online.liebertpub.com/doi/pdf/10.1089/cmb.2012.0022

http://bioinformatics.oxfordjournals.org/content/28/24/3169

Some new Mapping tool links:

GSNAP

http://research-pub.gene.com/gmap/

RMAP

http://rulai.cshl.edu/rmap/

mrsFAST

http://mrsfast.sourceforge.net/Home

http://sourceforge.net/projects/mrsfast/files/mrsfast-ultra-3.1.0/

BFAST

http://sourceforge.net/apps/mediawiki/bfast/index.php?title=Main_Page

SHRiMP (for AB SOLiD color-space reads)

http://compbio.cs.toronto.edu/shrimp/

RazerA 3

http://www.seqan.de/projects/razers/

Address of the bookmark: http://www.biomedcentral.com/1471-2105/14/184

Largest Genome Sequenced

Rahul Agarwal — Fri, 21 Mar 2014 13:57:19 -0500

The enormous size of the loblolly pine genome having 22 billion base pairs compared to only 3 billion in the human genome. In other words, it is seven times larger than a human’s and also the largest and the most complete conifer genome ever sequenced.

Related Paper:

http://genomebiology.com/2014/15/3/R59/abstract

Address of the bookmark: http://www.news.ucdavis.edu/search/news_detail.lasso?id=10859

New RNA Seq tool

Rahul Agarwal — Fri, 25 Apr 2014 10:59:04 -0500

"By removing the time-consuming step of read mapping, the authors reported, Sailfish able to provide quantification estimates 20–30 times faster than current methods without loss of accuracy."

Tool link:

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

Address of the bookmark: http://www.genengnews.com/gen-news-highlights/lightweight-algorithms-sail-through-rna-sequencing-data/81249765/

GenXPro GmbH

Rahul Agarwal — Thu, 22 May 2014 07:18:35 -0500

GenXPro GMbH is service provider for entire spectrum of nucleotide-based information of any biological sample. By combining intelligent data reduction techniques and latest next generation sequencing technologies, our service portfolio provides most accurate and cost efficient solutions for transcriptomic-, genomic- or epigenomic research.

GENXPRO GMBH, ALTENHÖFERALLEE 3, 60438 FRANKFURT MAIN, GERMANY

Website: http://www.genxpro.info/products_and_services/

PHONE: +49 (0)69- 95 73 97 10, FAX: +49 (0)69- 95 73 97 06

EMAIL: info@genxpro.de

Genomics and sequencing approach for identification of biomarkers to assess the efficacy of TGF-βRI inhibitors (of liver cancer) in vivo

Rahul Agarwal — Tue, 05 Aug 2014 13:55:32 -0500

Liver cancer is third leading cause of deaths and fourth most frequent occuring cancer worldwide. There are multiple signaling pathways responsible for causing cancer amongst which TGFb is most important cytokine whose signaling pathway promote cancer. However, main problem is to cure this cancer at late stage where we still have no treatment strategy to tackle this deadly cancer. Hence we need to find out new therapeutic target. One way is to look the relationships between mRNA, methylation and miRNA data of patients with different pathological conditions (cancer vs control either with inhibitor/not). MiRNA is small RNA molecules known to inhibit mRNA expression of particular gene by binding improperly to 3'UTR region of a gene and hence block binding of TF /translation of gene. CpG regions is known to located at promoter region of gene (5' UTR) and usually hypomethylated which allow to gene to transcribe and translate however sometime this region become hyper-methylated thats prevent expression of host gene. Thus , integration of these three data reveal new targets and pathways important for causing or preventing cancer and also reveal biomarker thats check the effects of inhibitor on signaling pathway underlying liver cancer.