Objective and Comprehensive Evaluation of Bisulfite Short Read Mapping Tools

Background. Large-scale bisulfite treatment and short reads sequencing technology allow comprehensive estimation of methylation states of Cs in the genomes of different tissues, cell types, and developmental stages. Accurate characterization of DNA methylation is essential for understanding genotype phenotype association, gene and environment interaction, diseases, and cancer. Aligning bisulfite short reads to a reference genome has been a challenging task. We compared five bisulfite short read mapping tools, BSMAP, Bismark, BS-Seeker, BiSS, and BRAT-BW, representing two classes of mapping algorithms (hash table and suffix/prefix tries). We examined their mapping efficiency (i.e., the percentage of reads that can be mapped to the genomes), usability, running time, and effects of changing default parameter settings using both real and simulated reads. We also investigated how preprocessing data might affect mapping efficiency. Conclusion. Among the five programs compared, in terms of mapping efficiency, Bismark performs the best on the real data, followed by BiSS, BSMAP, and finally BRAT-BW and BS-Seeker with very similar performance. If CPU time is not a constraint, Bismark is a good choice of program for mapping bisulfite treated short reads. Data quality impacts a great deal mapping efficiency. Although increasing the number of mismatches allowed can increase mapping efficiency, it not only significantly slows down the program, but also runs the risk of having increased false positives. Therefore, users should carefully set the related parameters depending on the quality of their sequencing data.

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Investigating bisulfite short-read mapping failure with hairpin bisulfite sequencing data

BMC Genomics ◽

10.1186/1471-2164-16-s11-s2 ◽

2015 ◽

Vol 16 (Suppl 11) ◽

pp. S2 ◽

Cited By ~ 3

Author(s):

Jacob Porter ◽

Ming-an Sun ◽

Hehuang Xie ◽

Liqing Zhang

Keyword(s):

Bisulfite Sequencing ◽

Sequencing Data ◽

Read Mapping ◽

Short Read ◽

Short Read Mapping ◽

Bisulfite Sequencing Data

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SEAL: a distributed short read mapping and duplicate removal tool

Bioinformatics ◽

10.1093/bioinformatics/btr325 ◽

2011 ◽

Vol 27 (15) ◽

pp. 2159-2160 ◽

Cited By ~ 85

Author(s):

L. Pireddu ◽

S. Leo ◽

G. Zanetti

Keyword(s):

Read Mapping ◽

Short Read ◽

Short Read Mapping

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Short Read Mapping: An Algorithmic Tour

Proceedings of the IEEE ◽

10.1109/jproc.2015.2455551 ◽

2017 ◽

Vol 105 (3) ◽

pp. 436-458 ◽

Cited By ~ 30

Author(s):

Stefan Canzar ◽

Steven L. Salzberg

Keyword(s):

Read Mapping ◽

Short Read ◽

Short Read Mapping

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PERHAPS: Paired-End short Reads-based HAPlotyping from next-generation Sequencing data

Briefings in Bioinformatics ◽

10.1093/bib/bbaa320 ◽

2020 ◽

Author(s):

Jie Huang ◽

Stefano Pallotti ◽

Qianling Zhou ◽

Marcus Kleber ◽

Xiaomeng Xin ◽

...

Keyword(s):

Next Generation Sequencing ◽

Snp Array ◽

Simple Approach ◽

Next Generation Sequencing Data ◽

Next Generation ◽

Sequencing Data ◽

Short Read ◽

Array Data ◽

Short Reads ◽

Generation Sequencing

Abstract The identification of rare haplotypes may greatly expand our knowledge in the genetic architecture of both complex and monogenic traits. To this aim, we developed PERHAPS (Paired-End short Reads-based HAPlotyping from next-generation Sequencing data), a new and simple approach to directly call haplotypes from short-read, paired-end Next Generation Sequencing (NGS) data. To benchmark this method, we considered the APOE classic polymorphism (*1/*2/*3/*4), since it represents one of the best examples of functional polymorphism arising from the haplotype combination of two Single Nucleotide Polymorphisms (SNPs). We leveraged the big Whole Exome Sequencing (WES) and SNP-array data obtained from the multi-ethnic UK BioBank (UKBB, N=48,855). By applying PERHAPS, based on piecing together the paired-end reads according to their FASTQ-labels, we extracted the haplotype data, along with their frequencies and the individual diplotype. Concordance rates between WES directly called diplotypes and the ones generated through statistical pre-phasing and imputation of SNP-array data are extremely high (>99%), either when stratifying the sample by SNP-array genotyping batch or self-reported ethnic group. Hardy-Weinberg Equilibrium tests and the comparison of obtained haplotype frequencies with the ones available from the 1000 Genome Project further supported the reliability of PERHAPS. Notably, we were able to determine the existence of the rare APOE*1 haplotype in two unrelated African subjects from UKBB, supporting its presence at appreciable frequency (approximatively 0.5%) in the African Yoruba population. Despite acknowledging some technical shortcomings, PERHAPS represents a novel and simple approach that will partly overcome the limitations in direct haplotype calling from short read-based sequencing.

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GPU-RMAP: Accelerating Short-Read Mapping on Graphics Processors

2010 13th IEEE International Conference on Computational Science and Engineering ◽

10.1109/cse.2010.29 ◽

2010 ◽

Cited By ~ 13

Author(s):

Ashwin M. Aji ◽

Liqing Zhang ◽

Wu-chun Feng

Keyword(s):

Graphics Processors ◽

Read Mapping ◽

Short Read ◽

Short Read Mapping

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gplas: a comprehensive tool for plasmid analysis using short-read graphs

Bioinformatics ◽

10.1093/bioinformatics/btaa233 ◽

2020 ◽

Vol 36 (12) ◽

pp. 3874-3876 ◽

Cited By ~ 1

Author(s):

Sergio Arredondo-Alonso ◽

Martin Bootsma ◽

Yaïr Hein ◽

Malbert R C Rogers ◽

Jukka Corander ◽

...

Keyword(s):

Large Scale ◽

Sequence Data ◽

Bacterial Genome ◽

Workflow Management ◽

Supplementary Information ◽

Whole Genome Sequencing Data ◽

Network Partitioning ◽

Sequencing Data ◽

Genetic Traits ◽

Short Read

Abstract Summary Plasmids can horizontally transmit genetic traits, enabling rapid bacterial adaptation to new environments and hosts. Short-read whole-genome sequencing data are often applied to large-scale bacterial comparative genomics projects but the reconstruction of plasmids from these data is facing severe limitations, such as the inability to distinguish plasmids from each other in a bacterial genome. We developed gplas, a new approach to reliably separate plasmid contigs into discrete components using sequence composition, coverage, assembly graph information and network partitioning based on a pruned network of plasmid unitigs. Gplas facilitates the analysis of large numbers of bacterial isolates and allows a detailed analysis of plasmid epidemiology based solely on short-read sequence data. Availability and implementation Gplas is written in R, Bash and uses a Snakemake pipeline as a workflow management system. Gplas is available under the GNU General Public License v3.0 at https://gitlab.com/sirarredondo/gplas.git. Supplementary information Supplementary data are available at Bioinformatics online.

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A new approach for approximate text search using genomic short-read mapping model

Proceedings of the 9th International Conference on Ubiquitous Information Management and Communication - IMCOM '15 ◽

10.1145/2701126.2701151 ◽

2015 ◽

Author(s):

Sung-Hwan Kim ◽

Hwan-Gue Cho

Keyword(s):

Text Search ◽

Read Mapping ◽

New Approach ◽

Short Read ◽

Mapping Model ◽

Short Read Mapping

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MOSAIK: A Hash-Based Algorithm for Accurate Next-Generation Sequencing Short-Read Mapping

PLoS ONE ◽

10.1371/journal.pone.0090581 ◽

2014 ◽

Vol 9 (3) ◽

pp. e90581 ◽

Cited By ~ 161

Author(s):

Wan-Ping Lee ◽

Michael P. Stromberg ◽

Alistair Ward ◽

Chip Stewart ◽

Erik P. Garrison ◽

...

Keyword(s):

Next Generation Sequencing ◽

Next Generation ◽

Read Mapping ◽

Short Read ◽

Short Read Mapping ◽

Generation Sequencing

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An Efficient GPUAccelerated Implementation of Genomic Short Read Mapping with BWAMEM

ACM SIGARCH Computer Architecture News ◽

10.1145/3039902.3039910 ◽

2017 ◽

Vol 44 (4) ◽

pp. 38-43 ◽

Cited By ~ 3

Author(s):

Ernst Joachim Houtgast ◽

VladMihai Sima ◽

Koen Bertels ◽

Zaid AlArs

Keyword(s):

Read Mapping ◽

Short Read ◽

Short Read Mapping

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Deconvolute individual genomes from metagenome sequences through short read clustering

PeerJ ◽

10.7717/peerj.8966 ◽

2020 ◽

Vol 8 ◽

pp. e8966 ◽

Cited By ~ 1

Author(s):

Kexue Li ◽

Yakang Lu ◽

Li Deng ◽

Lili Wang ◽

Lizhen Shi ◽

...

Keyword(s):

Large Scale ◽

False Negative ◽

Next Generation Sequencing Data ◽

Clustering Methods ◽

Sequencing Data ◽

Short Reads ◽

Clustering Problem ◽

Metagenome Assembly ◽

Real World Datasets ◽

Almost All

Metagenome assembly from short next-generation sequencing data is a challenging process due to its large scale and computational complexity. Clustering short reads by species before assembly offers a unique opportunity for parallel downstream assembly of genomes with individualized optimization. However, current read clustering methods suffer either false negative (under-clustering) or false positive (over-clustering) problems. Here we extended our previous read clustering software, SpaRC, by exploiting statistics derived from multiple samples in a dataset to reduce the under-clustering problem. Using synthetic and real-world datasets we demonstrated that this method has the potential to cluster almost all of the short reads from genomes with sufficient sequencing coverage. The improved read clustering in turn leads to improved downstream genome assembly quality.

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