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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]

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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