BOL: Related items

DNA tale of 3 to 4 years old Serbia boy

Rahul Agarwal — Tue, 26 Nov 2013 17:34:00 -0600

The genome of a young boy found underground at Mal’ta near Lake Baikal of eastern Siberia around 24,000 years ago came out as close relative of Europeans and Native Indians.

Link:

http://www.nytimes.com/2013/11/21/science/two-surprises-in-dna-of-boy-found-buried-in-siberia.html?_r=0

http://www.nature.com/nature/journal/vaop/ncurrent/full/nature12736.html

Genome of Rainbow Trout Sequenced

Rahul Agarwal — Fri, 25 Apr 2014 10:36:51 -0500

Major finding:

“In humans and most vertebrates the duplication events were older so there are fewer duplicated genes still present. Most of the duplicated genes get lost or modified so much that they are no longer recognizable as duplicates over time. In the trout and salmon we can see an earlier stage in the process and many duplicated genes are still present,” said Dr Gary Thorgaard of Washington State University, a co-author of the paper published in the journal Nature Communications.

Source:

http://www.sci-news.com/genetics/science-genome-rainbow-trout-01877.html

Real time Sequencing

Rahul Agarwal — Sun, 04 May 2014 18:16:42 -0500

“... we now know we can do high-throughput sequencing at any location on Earth,” Moroz said.

Source:

http://news.ufl.edu/2014/04/28/real-time-genome-sequencing-at-sea/

miRNA database and tools

Rahul Agarwal — Mon, 09 Jun 2014 07:58:40 -0500

Since few years miRNA has shown to play important role in therapeutic related research and also known to play vital role in controlling gene expression specifically at transcriptional and post-transcription levels. Here are some important DBs and tools related with miRNA:

miRNA Sequencing data analysis : http://tools.genxpro.net/omiras/

miRNApath( R based tool) : http://www.bioconductor.org/packages/release/bioc/html/miRNApath.html

miRWalk DB : http://www.umm.uni-heidelberg.de/apps/zmf/mirwalk/

TargetScanHuman : http://www.targetscan.org/

RNAhybrid : http://bibiserv.techfak.uni-bielefeld.de/rnahybrid/welcome.html

RNA22 predictor : http://cbcsrv.watson.ibm.com/rna22.html

miRNA predictor : http://www.microrna.org/microrna/home.do

Plant miRNA DB :http://bioinformatics.cau.edu.cn/PMRD/

miRBASE DB: http://www.mirbase.org/

Plant RNA predictor : http://plantgrn.noble.org/psRNATarget/

miRNA Interaction DB : http://starbase.sysu.edu.cn/

Sequencing based miRNA DB : http://mirgator.kobic.re.kr/

predicted A-to-I edited miRNA DB : http://microrna.osumc.edu/mireditar/

Animal, plant and virus miRNA DB : http://lemur.amu.edu.pl/share/php/mirnest/

Atlantic Salmon miRNAs DB : http://www.molgenv.com/ssa_mirnas_db_home.php

miRNA prediction on UTRs : http://genie.weizmann.ac.il/pubs/mir07/mir07_prediction.html

Idea of analysing miRNA Sequencing data :

http://www.illumina.com/applications/epigenetics/small_rna_analysis.ilmn

More:

http://www.bioconductor.org/help/search/index.html?q=miRNA+target

GraphMap - A highly sensitive and accurate mapper for long, error-prone reads

Rahul Agarwal — Mon, 06 Jul 2015 08:46:53 -0500

GraphMap is a novel mapper targeted at aligning long, error-prone third-generation sequencing data.
It is designed to handle Oxford Nanopore MinION 1d and 2d reads with very high sensitivity and accuracy, and also presents a significant improvement over the state-of-the-art for PacBio read mappers.

GraphMap was also designed for ease-of-use: the default parameters can handle a wide range of read lengths and error profiles, including: Illumina, PacBio and Oxford Nanopore.
This is an especially important feature for technologies where the error rates and error profiles can vary widely across, or even within, sequencing runs.

http://biorxiv.org/content/early/2015/06/10/020719

Address of the bookmark: https://github.com/isovic/graphmap

CovCal: Coverage / Read Count Calculator

Jit — Wed, 15 Jun 2016 18:08:13 -0500

Coverage / Read Count Calculator

Calculate how much sequencing you need to hit a target depth of coverage (or vice versa).

Instructions: set the read length/configuration and genome size, then select what you want to calculate.

Written by Stephen Turner, based on the Lander-Waterman formula, inspired by a similar calculator written by James Hadfield. Coverage is calculated as C=LN/G and reads as N=CG/L where C = Coverage (X),L = Read length (bp), G = Haploid genome size (bp), and N = Number of reads. Source code on GitHub.

Address of the bookmark: http://apps.bioconnector.virginia.edu/covcalc/

Grinder / Biogrinder - A versatile omics shotgun and amplicon sequencing read simulator

Jit — Wed, 24 May 2017 08:41:41 -0500

Grinder is a versatile program to create random shotgun and amplicon sequence libraries based on DNA, RNA or proteic reference sequences provided in a FASTA file.

Grinder can produce genomic, metagenomic, transcriptomic, metatranscriptomic, proteomic, metaproteomic shotgun and amplicon datasets from current sequencing technologies such as Sanger, 454, Illumina. These simulated datasets can be used to test the accuracy of bioinformatic tools under specific hypothesis, e.g. with or without sequencing errors, or with low or high community diversity. Grinder may also be used to help decide between alternative sequencing methods for a sequence-based project, e.g. should the library be paired-end or not, how many reads should be sequenced.

Address of the bookmark: https://sourceforge.net/projects/biogrinder/files/biogrinder/

LRSDAY: Long-read Sequencing Data Analysis for Yeasts

Poonam Mahapatra — Mon, 26 Aug 2019 18:07:33 -0500

Long-read sequencing technologies have become increasingly popular in genome projects due to their strengths in resolving complex genomic regions. As a leading model organism with small genome size and great biotechnological importance, the budding yeast, Saccharomyces cerevisiae, has many isolates currently being sequenced with long reads.

Address of the bookmark: https://github.com/yjx1217/LRSDAY

Choosing the Right NGS Sequencing Instrument for Your Study

Neel — Wed, 15 Jun 2022 00:37:29 -0500

The right sequencing instrument for your study depends on your project goal. Setting aside turnaround time and price, it essentially comes down to the numbers of reads and read length you need for your experiment. Below, we've described and compared metrics for each of the instruments available. If you’re new to high-throughput sequencing and have questions about how you should design your sequencing run, fill out our free consultation form and we'll get in touch with you to help.

More at https://genohub.com/ngs-instrument-guide/

Address of the bookmark: https://genohub.com/ngs-instrument-guide/

Compressive Genomics

Rahul Agarwal — Sun, 11 Aug 2013 11:13:58 -0500

The key to finding a solution is to notice that most genomicsequences differ by very little. It may well be that the number of complete genome sequences being stored is increasing rapidly, but the actual amount of new data is very small. In other words, a single DNA sequence isn't particularly compressible but a set of sequences shares so much in common that the redundancy can be used to store them in a much smaller storage space. (Source:e-article from Alex Armstrong)

http://www.i-programmer.info/news/181-algorithms/4537-a-new-dna-sequence-search-compressive-genomics.html

http://en.wikipedia.org/wiki/Compression_of_Genomic_Re-Sequencing_Data

http://www.nature.com/nbt/journal/v30/n7/full/nbt.2241.html

http://bioinformatics.oxfordjournals.org/content/29/13/i283.full

http://groups.csail.mit.edu/cb/cast/