Cloud-MAQ: The cloud-enabled scalable whole genome reference Assembly application

Talukder, Asoke K.; Gandham, Santhosh; Prahalad, H. A; Bhattacharyya, Nitai P.

doi:10.1109/wocn.2010.5587308

Cited by 5 publications

(6 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The amplification of the alleles is done using two pairs of primers. This process involves overlapping of the primer pairs so that it matches the pairs but not to the alternative allele for the SNP [15][16][17][18]. The conventional techniques for SNP detection rely on gel electrophoresis for the fragment analysis [19][20][21].…”

Section: Of 11mentioning

confidence: 99%

See 1 more Smart Citation

Nucleotide Identification in DNA Using Dielectrophoresis Spectroscopy

et al. 2019

View full text Add to dashboard Cite

We show that negative dielectrophoresis (DEP) spectroscopy is an effective transduction mechanism of a biosensor for the detection of single nucleotide polymorphism (SNP) in a short DNA strand. We observed a frequency dependence of the negative DEP force applied by interdigitated electrodes to polystyrene microspheres (PM) with respect to changes in both the last and the second-to-last nucleotides of a single-strand DNA bound to the PM. The drift velocity of PM functionalized to single-strand DNA, which is proportional to the DEP force, was measured at the frequency range from 0.5 MHz to 2 MHz. The drift velocity was calculated using a custom-made automated software using real time image processing technique. This technology for SNP genotyping has the potential to be used in the diagnosis and the identification of genetic variants associated with diseases.

show abstract

Section: Of 11mentioning

confidence: 99%

“…This technique is based on the Bayesian statistical model that includes error probability and mapping qualities from the quality scores of the sequence. Although minimum order quality (MOQ) [16] is efficient and highly sensitive, the high probability of sequencing errors in this method makes it less reliable than other methods. 2…”

Section: Introductionmentioning

confidence: 99%

Nucleotide Identification in DNA Using Dielectrophoresis Spectroscopy

et al. 2019

View full text Add to dashboard Cite

show abstract

“…Several popular alignment tools have been adapted to run in clouds using Hadoop's MapReduce to execute code in parallel (Cloud-MAQ [22], Cloud-BLAST [15]). MapReduce's performance can be affected by the large amounts of data that has to be uploaded in the cloud, before executing the processing step.…”

Section: Alignment In the Cloudmentioning

confidence: 99%

“…Privacy-preserving alignment can be obtained in mainly two ways: rely on plaintext conventional algorithms in a secure environment (e.g. local computer, private cloud) [22,14], or protect data through cryptographic methods. In the former there is always a risk for an adversary to get access to the machines, and therefore to the sensitive data.…”

Section: Towards a Differentiated Protection Of Genomic Datamentioning

confidence: 99%

Cloud-Assisted Read Alignment and Privacy

Fernandes

Decouchant

Couto

et al. 2017

11th International Conference on Practical Applications of Computational Biology &Amp; Bioinformatics

View full text Add to dashboard Cite

Thanks to the rapid advances in sequencing technologies, genomic data is now being produced at an unprecedented rate. To adapt to this growth, several algorithms and paradigm shifts have been proposed to increase the throughput of the classical DNA workflow, e.g. by relying on the cloud to perform CPU intensive operations. However, the scientific community raised an alarm due to the possible privacy-related attacks that can be executed on genomic data. In this paper we review the state of the art in cloud-based alignment algorithms that have been developed for performance. We then present several privacy-preserving mechanisms that have been, or could be, used to align reads at an incremental performance cost. We finally argue for the use of risk analysis throughout the DNA workflow, to strike a balance between performance and protection of data.

show abstract

“…Hadoop-BLAST (Nachankar and Arvind, 2011) uses Hadoop to efficiently distribute tasks and reliably transmit data in sequence alignment process. Cloud-MAQ (Talukder et al, 2010) makes MAQ parallel and scalable through Hadoop and enhances the performance of MAQ significantly.…”

Section: Mapreduce Modelmentioning

confidence: 99%

Hadoop-RINS - A Hadoop Accelerated Pipeline for Rapid Nonhuman Sequence Identification

Li¹,

Liu²,

Wang

et al. 2013

Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms

View full text Add to dashboard Cite

Sequencing data increase rapidly in recent years with the development of high-throughput sequencing technology. Using parallel computing to accelerate the computation is an important way to process the large volume of sequence data. RINS is a pipeline used to identify nonhuman sequences in deep sequencing datasets. It uses user-provided microbial reference genomes to reduce the number of reads to be processed and improve the processing speed. But all of its steps run serially. As a result, the processing speed of RINS slows down sharply as the sequencing data and reference genomes increase. In this article, we report a pipeline that processes sequencing data parallel through Hadoop. By comparing the runtime using same dataset, Hadoop-RINS is proved to be significantly faster than RINS with the same computation result.

show abstract

Cloud-MAQ: The cloud-enabled scalable whole genome reference Assembly application

Cited by 5 publications

References 4 publications

Nucleotide Identification in DNA Using Dielectrophoresis Spectroscopy

Nucleotide Identification in DNA Using Dielectrophoresis Spectroscopy

Cloud-Assisted Read Alignment and Privacy

Hadoop-RINS - A Hadoop Accelerated Pipeline for Rapid Nonhuman Sequence Identification

Contact Info

Product

Resources

About