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RNA-seq analysis

RNAIndel: A tool to identify somatic indels from tumor RNA-seq data

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RNAIndel-predict somatic indels in tumor rna-seq

It is a challenging task to discover somatic coding indels that are generated during the preparation of the PCR-based RNA-seq library. A new tool called RNAIndel [1] has been developed for this purpose.

RNAIndel predicts indels in RNA-seq data and classifies them as somatic, germline, and artifact indels. RNAIndel implements a biological effect in a machine learning framework and predicts somatic indels with around 88-100% accuracy. RNAIndel is composed of 31 features in total including a count of repeats, relative indel location, and so on.

RNAIndel takes the RNA-seq BAM file as input mapped by STAR software [2]. After reading the input file, all indels are annotated using RefSeq [3] isoforms followed by querying a custom germline database for exact and equivalent matches. Indels having greater than or equal to two reads are predicted and classifies as single-nucleotide (s-indel) and multi-nucleotide (m-indel). Finally, it generates output in the VCF file consisting of indel entries, supporting reads, predicted class, and probability.

For further details, read here.


References

  1. Hagiwara, K., Ding, L., Edmonson, M. N., Rice, S. V., Newman, S., Easton, J., … & Zhang, J. (2020). RNAIndel: discovering somatic coding indels from tumor RNA-Seq data. Bioinformatics36(5), 1382-1390.
  2. Dobin, A., Davis, C. A., Schlesinger, F., Drenkow, J., Zaleski, C., Jha, S., … & Gingeras, T. R. (2013). STAR: ultrafast universal RNA-seq aligner. Bioinformatics29(1), 15-21.
  3. O’Leary, N. A., Wright, M. W., Brister, J. R., Ciufo, S., Haddad, D., McVeigh, R., … & Astashyn, A. (2016). Reference sequence (RefSeq) database at NCBI: current status, taxonomic expansion, and functional annotation. Nucleic acids research44(D1), D733-D745.

Tariq is founder of Bioinformatics Review and CEO at IQL Technologies. His areas of expertise include algorithm design, phylogenetics, MicroArray, Plant Systematics, and genome data analysis. If you have questions, reach out to him via his homepage.

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RNA-seq analysis

Pathonoia- A new tool to detect pathogens in RNA-seq data.

Dr. Muniba Faiza

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Pathonoia- A new tool to detect pathogens in RNA-seq data.

Detecting viruses and bacteria in RNA-seq data with less false positive rate is a difficult task. A new tool is introduced to detect pathogens in RNA-seq data with high precision and recall known as Pathonoia [1].

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RNA-seq analysis

RNAdetector- New Tool for RNA-Seq Data Analysis

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RNAdetector- New Tool for RNA-Seq Data Analysis

In this article, we discuss a new tool that is developed for RNA-Seq data analysis. A new tool called RNAdetector [1] is developed for RNA-Seq data analysis. (more…)

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RNA-seq analysis

Installing TopHat2 on Ubuntu

Dr. Muniba Faiza

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Installing tophat2 on Ubuntu

TopHat is one of the most widely used tools for RNA-seq reads to map splice junction [1]. It uses Bowtie to align mammalian genomes. The older versions of TopHat require the separate installation of SAMTools. But the versions 2.0 onwards come with an inbuilt stable SAMTools package. In this article, we will install TopHat2.1.1. on Ubuntu. (more…)

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RNA-seq analysis

Differential Gene Expression Analysis of RNA-Seq data using MeV

Dr. Muniba Faiza

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RNA-Seq data analysis

Differential gene expression analysis helps in discovering quantitative changes in the expression levels between the experimental groups. For that, statistical testing is done using various software. In this article, we will analyze RNA seq count data using the edgeR module present in the Multiple Experiment Viewer (MeV) [1,2]. (more…)

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RNA-seq analysis

Most widely used web servers/software for single-cell RNA-seq analysis

Dr. Muniba Faiza

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single-cell rna-seq

Gene expression in single cells is measured using single-cell RNA sequencing technology. It helps in finding new and available cell types of different tissues and organs. In this article, the most widely used web servers and software for single-cell RNA-seq analysis are discussed. (more…)

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