ReHap: AN INTEGRATED SYSTEM FOR THE HAPLOTYPE ASSEMBLY PROBLEM FROM SHOTGUN SEQUENCING DATA

2010 ◽  
Keyword(s):  
Shotgun Sequencing ◽  
Integrated System ◽  
Sequencing Data ◽  
Haplotype Assembly ◽  
Assembly Problem

scholarly journals Accurate and Strict Identification of Probiotic Species Based on Coverage of Whole-Metagenome Shotgun Sequencing Data

2019 ◽  
Vol 10 ◽  
Author(s):  
Donghyeok Seol ◽  
So Yun Jhang ◽  
Hyaekang Kim ◽  
Se-Young Kim ◽  
Hyo-Sun Kwak ◽  
...  
Keyword(s):  
Shotgun Sequencing ◽  
Sequencing Data

scholarly journals phylogenize: correcting for phylogeny reveals genes associated with microbial distributions

2019 ◽  
Vol 36 (4) ◽  
pp. 1289-1290
Author(s):  
Patrick H Bradley ◽  
Katherine S Pollard
Keyword(s):  
Community Composition ◽  
Human Microbiome ◽  
Human Microbiome Project ◽  
Shotgun Sequencing ◽  
Supplementary Information ◽  
Phylogenetic Comparative Methods ◽  
Supplementary Data ◽  
Sequencing Data ◽  
Phylogenetic Regression ◽  
Project Data

Abstract Summary Phylogenetic comparative methods are powerful but presently under-utilized ways to identify microbial genes underlying differences in community composition. These methods help to identify functionally important genes because they test for associations beyond those expected when related microbes occupy similar environments. We present phylogenize, a pipeline with web, QIIME 2 and R interfaces that allows researchers to perform phylogenetic regression on 16S amplicon and shotgun sequencing data and to visualize results. phylogenize applies broadly to both host-associated and environmental microbiomes. Using Human Microbiome Project and Earth Microbiome Project data, we show that phylogenize draws similar conclusions from 16S versus shotgun sequencing and reveals both known and candidate pathways associated with host colonization. Availability and implementation phylogenize is available at https://phylogenize.org and https://bitbucket.org/pbradz/phylogenize. Supplementary information Supplementary data are available at Bioinformatics online.

Self-organizing map approaches for the haplotype assembly problem

2009 ◽  
Vol 79 (10) ◽  
pp. 3026-3037 ◽  
Author(s):  
Ling-Yun Wu ◽  
Zhenping Li ◽  
Rui-Sheng Wang ◽  
Xiang-Sun Zhang ◽  
Luonan Chen
Keyword(s):  
Self Organizing Map ◽  
Haplotype Assembly ◽  
Assembly Problem ◽  
Self Organizing

scholarly journals A Bacterial Analysis Platform: An Integrated System for Analysing Bacterial Whole Genome Sequencing Data for Clinical Diagnostics and Surveillance

PLoS ONE ◽  
2016 ◽  
Vol 11 (6) ◽  
pp. e0157718 ◽  
Author(s):  
Martin Christen Frølund Thomsen ◽  
Johanne Ahrenfeldt ◽  
Jose Luis Bellod Cisneros ◽  
Vanessa Jurtz ◽  
Mette Voldby Larsen ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Clinical Diagnostics ◽  
Integrated System ◽  
Whole Genome Sequencing Data ◽  
Whole Genome ◽  
Sequencing Data ◽  
Analysis Platform

scholarly journals The JCVI standard operating procedure for annotating prokaryotic metagenomic shotgun sequencing data

2010 ◽  
Vol 2 (2) ◽  
pp. 229-237 ◽  
Author(s):  
David M. Tanenbaum ◽  
Johannes Goll ◽  
Sean Murphy ◽  
Prateek Kumar ◽  
Nikhat Zafar ◽  
...  
Keyword(s):  
Operating Procedure ◽  
Standard Operating Procedure ◽  
Shotgun Sequencing ◽  
Sequencing Data ◽  
Standard Operating

scholarly journals Complete genome assemblies for three variants of the Wolbachia endosymbiont of Drosophila melanogaster

2019 ◽  
Author(s):  
Preston J. Basting ◽  
Casey M. Bergman
Keyword(s):  
Drosophila Melanogaster ◽  
Complete Genome ◽  
Shotgun Sequencing ◽  
Sequencing Data ◽  
Wolbachia Pipientis ◽  
Long Read ◽  
Wolbachia Endosymbiont ◽  
Genome Assemblies

ABSTRACTHere we report genome assemblies for three strains of Wolbachia pipientis assembled from unenriched, unfiltered long-read shotgun sequencing data of geographically distinct strains of Drosophila melanogaster. Our simple methodology can be applied to long-read datasets of other Wolbachia-infected species to produce complete assemblies for this important model symbiont.

scholarly journals Selecting Reads for Haplotype Assembly

2016 ◽  
Author(s):  
Sarah O. Fischer ◽  
Tobias Marschall
Keyword(s):  
Next Generation Sequencing ◽  
Error Correction ◽  
Heuristic Algorithm ◽  
Next Generation Sequencing Data ◽  
Sequencing Data ◽  
Minimum Error ◽  
Haplotype Assembly ◽  
Maximum Coverage ◽  
Processing Step ◽  
Generation Sequencing

AbstractHaplotype assembly or read-based phasing is the problem of reconstructing both haplotypes of a diploid genome from next-generation sequencing data. This problem is formalized as the Minimum Error Correction (MEC) problem and can be solved using algorithms such as WhatsHap. The runtime of WhatsHap is exponential in the maximum coverage, which is hence controlled in a pre-processing step that selects reads to be used for phasing. Here, we report on a heuristic algorithm designed to choose beneficial reads for phasing, in particular to increase the connectivity of the phased blocks and the number of correctly phased variants compared to the random selection previously employed in by WhatsHap. The algorithm we describe has been integrated into the WhatsHap software, which is available under MIT licence from https://bitbucket.org/whatshap/whatshap.

scholarly journals Multiomic Strategies Reveal Diversity and Important Functional Aspects of Human Gut Microbiome

2018 ◽  
Vol 2018 ◽  
pp. 1-13 ◽  
Author(s):  
Ravi Ranjan ◽  
Asha Rani ◽  
Patricia W. Finn ◽  
David L. Perkins
Keyword(s):  
Sequence Data ◽  
Bacterial Species ◽  
Abundant Species ◽  
Shotgun Sequencing ◽  
Sequencing Analysis ◽  
Sequencing Data ◽  
Illumina Platform ◽  
Shotgun Metagenomics ◽  
Functional Aspects ◽  
Detectable Bias

It is well accepted that dysbiosis of microbiota is associated with disease; however, the biological mechanisms that promote susceptibility or resilience to disease remain elusive. One of the major limitations of previous microbiome studies has been the lack of complementary metatranscriptomic (functional) data to complement the interpretation of metagenomics (bacterial abundance). The purpose of this study was twofold, first to evaluate the bacterial diversity and differential gene expression of gut microbiota using complementary shotgun metagenomics (MG) and metatranscriptomics (MT) from same fecal sample. Second, to compare sequence data using different Illumina platforms and with different sequencing parameters as new sequencers are introduced, and to determine if the data are comparable on different platforms. In this study, we perform ultradeep metatranscriptomic shotgun sequencing for a sample that we previously analyzed with metagenomics shotgun sequencing. We performed sequencing analysis using different Illumina platforms, with different sequencing and analysis parameters. Our results suggest that use of different Illumina platform did not lead to detectable bias in the sequencing data. The analysis of the sample using MG and MT approach shows that some species genes are highly represented in the MT than in the MG, indicating that some species are highly metabolically active. Our analysis also shows that ~52% of the genes in the metagenome are in the metatranscriptome and therefore are robustly expressed. The functions of the low and rare abundance bacterial species remain poorly understood. Our observations indicate that among the low abundant species analyzed in this study some were found to be more metabolically active compared to others, and can contribute distinct profiles of biological functions that may modulate the host-microbiota and bacteria-bacteria interactions.

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