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Claudia Calabrese Marina Mangiulli Caterina Manzari Anna Maria Paluscio Mariano Francesco Caratozzolo Flaviana Marzano Ivana Kurelac Anna Maria D’Erchia Domenica D’Elia Flavio Licciulli Sabino Liuni Ernesto Picardi Marcella Attimonelli Giuseppe Gasparre Anna Maria Porcelli Graziano Pesole Elisabetta Sbisà Apollonia Tullo 《BMC genomics》2013,14(1)
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Jesper R. G?din Ferdinand M. van’t Hooft Per Eriksson Lasse Folkersen 《BMC bioinformatics》2015,16(1)
Background
One aspect in which RNA sequencing is more valuable than microarray-based methods is the ability to examine the allelic imbalance of the expression of a gene. This process is often a complex task that entails quality control, alignment, and the counting of reads over heterozygous single-nucleotide polymorphisms. Allelic imbalance analysis is subject to technical biases, due to differences in the sequences of the measured alleles. Flexible bioinformatics tools are needed to ease the workflow while retaining as much RNA sequencing information as possible throughout the analysis to detect and address the possible biases.Results
We present AllelicImblance, a software program that is designed to detect, manage, and visualize allelic imbalances comprehensively. The purpose of this software is to allow users to pose genetic questions in any RNA sequencing experiment quickly, enhancing the general utility of RNA sequencing. The visualization features can reveal notable, non-trivial allelic imbalance behavior over specific regions, such as exons.Conclusions
The software provides a complete framework to perform allelic imbalance analyses of aligned RNA sequencing data, from detection to visualization, within the robust and versatile management class, ASEset.Electronic supplementary material
The online version of this article (doi:10.1186/s12859-015-0620-2) contains supplementary material, which is available to authorized users. 相似文献14.
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Background
The tremendous output of massive parallel sequencing technologies requires automated robust and scalable sample preparation methods to fully exploit the new sequence capacity.Methodology
In this study, a method for automated library preparation of RNA prior to massively parallel sequencing is presented. The automated protocol uses precipitation onto carboxylic acid paramagnetic beads for purification and size selection of both RNA and DNA. The automated sample preparation was compared to the standard manual sample preparation.Conclusion/Significance
The automated procedure was used to generate libraries for gene expression profiling on the Illumina HiSeq 2000 platform with the capacity of 12 samples per preparation with a significantly improved throughput compared to the standard manual preparation. The data analysis shows consistent gene expression profiles in terms of sensitivity and quantification of gene expression between the two library preparation methods. 相似文献16.
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