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Next Generation Sequencing (NGS)

The high demand for low-cost sequencing has driven the development of high-throughput sequencing, which also goes by the term Next Generation Sequencing (NGS). Thousands or millions of sequences are concurrently produced in a single next-generation sequencing process. Next generation sequencing has become a commodity. [Source: WikiBooks]

Vicinal

Submitted by ChenLiang on Sun, 09/10/2017 - 20:21

Non-coding (nc)RNAs are important structural and regulatory molecules. Accurate determination of the primary sequence and secondary structure of ncRNAs is important for understanding their functions. During cDNA synthesis, RNA 3' end stem-loops can self-prime reverse transcription, creating RNA-cDNA chimeras. We found that chimeric RNA-cDNA fragments can also be detected at 5' end stem-loops, although at much lower frequency.

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miRSeq

Submitted by ChenLiang on Fri, 09/02/2016 - 21:59

MicroRNAs (miRNAs) present diverse regulatory functions in a wide range of biological activities. Studies on miRNA functions generally depend on determining miRNA expression profiles between libraries by using a next-generation sequencing (NGS) platform. Currently, several online web services are developed to provide small RNA NGS data analysis. However, the submission of large amounts of NGS data, conversion of data format, and limited availability of species bring problems. In this study, we developed miRSeq to provide alternatives.

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miFRame

Submitted by ChenLiang on Fri, 09/02/2016 - 21:59

While in the past decades nucleic acid analysis has been predominantly carried out using quantitative low- and high-throughput approaches such as qRT-PCR and microarray technology, next-generation sequencing (NGS) with its single base resolution is now frequently applied in DNA and RNA testing. Especially for small non-coding RNAs such as microRNAs there is a need for analysis and visualization tools that facilitate interpretation of the results also for clinicians.

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SAMMate

Submitted by ChenLiang on Fri, 09/02/2016 - 21:59

Next Generation Sequencing (NGS) technology generates tens of millions of short reads for each DNA/RNA sample. A key step in NGS data analysis is the short read alignment of the generated sequences to a reference genome. Although storing alignment information in the Sequence Alignment/Map (SAM) or Binary SAM (BAM) format is now standard, biomedical researchers still have difficulty accessing this information.

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miRMaster

Submitted by ChenLiang on Tue, 01/09/2018 - 17:27

Abstract is not available.[1]

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DREAM

Submitted by ChenLiang on Fri, 09/02/2016 - 21:59

detecting RNA editing associated with microRNAs, is a webserver for the identification of mature microRNA editing events using deep sequencing data. Raw microRNA sequencing reads can be provided as input, the reads are aligned against the genome and custom scripts process the data, search for potential editing sites and assess the statistical significance of the findings. The output is a text file with the location and the statistical description of all the putative editing sites detected.[1]

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miRSeqNovel

Submitted by ChenLiang on Fri, 09/02/2016 - 21:59

We present miRSeqNovel, an R based workflow for miRNA sequencing data analysis. miRSeqNovel can process both colorspace (SOLiD) and basespace (Illumina/Solexa) data by different mapping algorithms. It finds differentially expressed miRNAs and gives conservative prediction of novel miRNA candidates with customized parameters. miRSeqNovel is freely available at http://sourceforge.net/projects/mirseq/files.[1]

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MicroRazerS

Submitted by ChenLiang on Fri, 09/02/2016 - 21:59

Deep sequencing has become the method of choice for determining the small RNA content of a cell. Mapping the sequenced reads onto their reference genome serves as the basis for all further analyses, namely for identification and quantification. A method frequently used is Mega BLAST followed by several filtering steps, even though it is slow and inefficient for this task. Also, none of the currently available short read aligners has established itself for the particular task of small RNA mapping.

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MLSeq

Submitted by ChenLiang on Sun, 09/10/2017 - 17:14

RNA sequencing (RNA-Seq) is a powerful technique for the gene-expression profiling of organisms that uses the capabilities of next-generation sequencing technologies. Developing gene-expression-based classification algorithms is an emerging powerful method for diagnosis, disease classification and monitoring at molecular level, as well as providing potential markers of diseases. Most of the statistical methods proposed for the classification of gene-expression data are either based on a continuous scale (eg. microarray data) or require a normal distribution assumption.

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miRPursuit

Submitted by ChenLiang on Sun, 09/10/2017 - 20:28

miRPursuit is a pipeline developed for running end-to-end analyses of high-throughput small RNA (sRNA) sequence data in model and nonmodel plants, from raw data to identified and annotated conserved and novel sequences. It consists of a series of UNIX shell scripts, which connect open-source sRNA analysis software. The involved parameters can be combined with convenient workflow management by users without advanced computational skills.

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