The huge amount of transcript data produced by high-throughput sequencing requires the development and implementation of suitable bioinformatic workflows for their analysis and interpretation. These analysis workflows, including different modules, should be specifically designed also based on the sequencing platform (Roche 454, Illumina, SOLiD) and the nature of the data (polyA or total RNA fraction, strand specificity). In the case of cDNA obtained from a total RNA preparation, in addition to polyadenylated protein coding mRNAs, a great variety of transcript sequences can be obtained, including ribosomal RNAs, mitochondrial transcripts and a large variety of functional non coding RNAs (ncRNAs). To deal with these data the analysis workflow should include specific modules to distinguish ncRNAs fractions from the large number of other functional proteincoding transcripts. To this aim we developed an analysis pipeline that, given as input a large collection of reads (particularly from Roche 454), provides the expression profile at qualitative and quantitative level of human mtDNA, ribosomal RNAs, ncRNAs and protein coding mRNAs.

A bioinformatics workflow for the analysis of transcriptome data generated by deep-sequencing

D'Elia D;Grillo G;Liuni S;Tullo A;Pesole G
2010

Abstract

The huge amount of transcript data produced by high-throughput sequencing requires the development and implementation of suitable bioinformatic workflows for their analysis and interpretation. These analysis workflows, including different modules, should be specifically designed also based on the sequencing platform (Roche 454, Illumina, SOLiD) and the nature of the data (polyA or total RNA fraction, strand specificity). In the case of cDNA obtained from a total RNA preparation, in addition to polyadenylated protein coding mRNAs, a great variety of transcript sequences can be obtained, including ribosomal RNAs, mitochondrial transcripts and a large variety of functional non coding RNAs (ncRNAs). To deal with these data the analysis workflow should include specific modules to distinguish ncRNAs fractions from the large number of other functional proteincoding transcripts. To this aim we developed an analysis pipeline that, given as input a large collection of reads (particularly from Roche 454), provides the expression profile at qualitative and quantitative level of human mtDNA, ribosomal RNAs, ncRNAs and protein coding mRNAs.
2010
Istituto di Tecnologie Biomediche - ITB
978-88-6194-079-6
Bioinformatics; Conference; Proceedings
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/152021
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