BOL: Related items

320000 viruses in mammals yet to sequenced in future!!!

Rahul Agarwal — Tue, 03 Sep 2013 08:35:30 -0500

With current biological technique improvements, finally it is now possible to look at millions of unknown viruses at genomic level and understand the mechanism. According to available data, close to 70 per cent of emerging viral diseases such as HIV/AIDS, West Nile, Ebola, SARS, and influenza, are zoonoses - infections of animals that cross into humans.

To address the challenges of describing and estimating virodiversity, a team of investigators from Center for Infection and Immunity (CII) and EcoHealth Alliance began in jungles of Bangladesh - home to the flying fox.

Reference:

http://economictimes.indiatimes.com/news/news-by-industry/et-cetera/mammals-harbour-at-least-320000-new-viruses/articleshow/22253268.cms

http://www.bbc.co.uk/news/science-environment-23932400

RNA Bioinformatics and High Throughput Analysis Jena

Sat, 09 Nov 2013 20:03:56 -0600

Research Topics:

High Throughput Sequencing Analysis
Comparative Genomics
Identification and Annotation of Non-coding RNAs
Bioinformatic Analysis and System Biology of Viruses
Coevolution of Proteins and RNAs
Algorithmic Bioinformatics
Phylogenetic Analysis

http://www.rna.uni-jena.de/index.php

Bio-Rad Acquires GnuBIO

Rahul Agarwal — Sat, 19 Apr 2014 10:36:36 -0500

http://www.businesswire.com/news/home/20140411005331/en/Bio-Rad-Acquires-GnuBIO-Developer-Droplet-Based-DNA-Sequencing#.U1KXnPm1b8o

Deadly Human Pathogen Cryptococcus Sequenced

Rahul Agarwal — Fri, 25 Apr 2014 11:02:21 -0500

"Now, researchers have sequenced the entire genome and all the RNA products of the most important pathogenic lineage of Cryptococcus neoformans, a strain called H99. The results, which appear in PLOS Genetics, also describe a number of genetic changes that can occur after laboratory handling of H99 that make it more susceptible to stress, hamper its ability to sexually reproduce and render it less virulent."

Source:

http://www.biosciencetechnology.com/news/2014/04/deadly-human-pathogen-cryptococcus-fully-sequenced

Paper:

http://www.plosgenetics.org/article/info%3Adoi%2F10.1371%2Fjournal.pgen.1004292

Drawback of Exome Sequencing

Rahul Agarwal — Mon, 02 Jun 2014 05:46:43 -0500

Dr Eric Londin, Assistant Professor, Thomas Jefferson University, USA, stated that analysis of 44 exome datasets from four different testing kits showed that they missed a high proportion of clinically relevant regions in the 56 ACMG genes. "At least one gene in each exome method was missing more than 40 percent of disease-causing genetic variants, and we found that the worst-performing method missed more than 90 percent of such variants in four of the 56 genes," he says.

Source: http://www.eurekalert.org/pub_releases/2014-05/esoh-pco052914.php

Pathway Analysis

Rahul Agarwal — Fri, 03 Oct 2014 08:51:13 -0500

Pathway Analysis is usually performed with aim to enrich the genes with their functional information and reveal the underlying biological mechanisms pursue by genes. Pathway Analysis is not only limited to what biological pathways a particular set of expressed genes follow but also to disclose the relationships between these genes. With availability of more genomics, transcriptomics and proteomics data, interactions between genes involve in multiple pathways become more clear and also relationships between the genes, their transcripts, and their gene products. However, existing tools and dbs mainly based on knowledge driven approach in which pathways will be identified by finding the correlation between the information in one of the pathway knowledge databases (KEGG,Reactome,Panther,BioCarta, Panther,GO,NCI,WikiPathways,etc) and gene expression result for a specific conditions for instance tumor, obesity , cold resistant crops/plants, etc.

Introductory Articles/ppt/sources:

http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.1002375

http://bioinformatics.mdanderson.org/MicroarrayCourse/Lectures09/Pathway%20Analysis.pdf

http://gettinggeneticsdone.blogspot.de/2012/03/pathway-analysis-for-high-throughput.html

http://davetang.org/muse/tag/pathway/

https://www.biostars.org/p/42219/

http://bioinformatics.ca//files/public/Pathways_2014_Module4_v2.pdf

http://bioinformatics.ca//files/public/Pathways_2014_Module2.pdf

Impotant Database and Tools:

GeneMANIA, Cytoscape, IPA and Metacore (Commerical ), Pathway Commons, Reactome ,Panther, BioCyc, WikiPathways, Pathvisio, KEGG, NCI, Stringdb, Amigo, WebGestalt ,ConsensusPathDB ,GSEA,Blast2go

Popular R based tools:

Reactome.db, ReactomePA, ClusterProfiler, Gage, SPIA, topGO, Pathview,DOSE,GOStat

More:

http://www.bioconductor.org/help/search/index.html?q=Enrichment+analysis+

cutadapt

Radha Agarkar — Fri, 13 May 2016 04:54:50 -0500

Cutadapt finds and removes adapter sequences, primers, poly-A tails and other types of unwanted sequence from your high-throughput sequencing reads.

Cleaning your data in this way is often required: Reads from small-RNA sequencing contain the 3’ sequencing adapter because the read is longer than the molecule that is sequenced. Amplicon reads start with a primer sequence. Poly-A tails are useful for pulling out RNA from your sample, but often you don’t want them to be in your reads.

Cutadapt helps with these trimming tasks by finding the adapter or primer sequences in an error-tolerant way. It can also modify and filter reads in various ways. Adapter sequences can contain IUPAC wildcard characters. Also, paired-end reads and even colorspace data is supported. If you want, you can also just demultiplex your input data, without removing adapter sequences at all.

Cutadapt comes with an extensive suite of automated tests and is available under the terms of the MIT license.

If you use cutadapt, please cite DOI:10.14806/ej.17.1.200 .

Address of the bookmark: https://cutadapt.readthedocs.io/en/stable/installation.html#quickstart

GAM-NGS: genomic assemblies merger for next generation sequencing

Jit — Fri, 19 May 2017 07:44:14 -0500

GAM-NGS is a tool able to merge two or more assemblies in order to improve contiguity and correctness. It can be used on all NGS-based assembly projects and it shows its full potential with multi-library Illumina-based projects. With more than 20 available assemblers it is hard to select the best tool. In this context we propose a tool that improves assemblies (and, as a by-product, perhaps even assemblers) by merging them and selecting the generating that is most likely to be correct.

Address of the bookmark: https://github.com/vice87/gam-ngs

simNGS and simLibrary – Software for Simulating Next-Gen Sequencing Data

Jit — Tue, 28 Nov 2017 06:49:11 -0600

simNGS is software for simulating observations from Illumina sequencing machines using the statistical models behind the AYB base-calling software. By default, observations only incorporate noise due to sequencing and do not incorporate effects from more esoteric sources of noise that may be present in real data ("dust", bubbles, merged clusters, sequence-heterogeneous clusters, etc). Many of these additional sources may optionally applied.

simNGS takes fasta format sequences and a file describing the covariance of noise between bases and cycles observed in an actual run of the machine, randomly generates noisy intensities representing the signals for the sequence at each cycle and calculates likelihoods for all possible base calls.

Address of the bookmark: https://www.ebi.ac.uk/goldman-srv/simNGS/

Earth BioGenome Project

Jit — Wed, 25 Apr 2018 07:48:56 -0500

The central goal of the Earth BioGenome Project is to understand the evolution and organization of life on our planet by sequencing and functionally annotating the genomes of 1.5 million known species of eukaryotes, a massive group that includes plants, animals, fungi and other organisms whose cells have a nucleus that houses their chromosomal DNA. To date, the genomes of less than 0.2 percent of eukaryotic species have been sequenced.

More at https://www.ucdavis.edu/news/earth-biogenome-project-aims-sequence-dna-all-complex-life