Comparison of RNA-seq and Microarray Platforms for Splice Event Detection using a Cross-Platform Algorithm [Junction Arrays]
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PROVIDER: PRJNA413297 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:In this study, we compare the performance of RNA-seq (Illumina HiSeq) and junction arrays (Affymetrix Human Transcriptome array) for the analysis of splicing events. Three different cell lines were treated with CX-4945, a drug that severely affects splicing. To make a fair comparison, we developed EventPointer, an algorithm that detects and labels alternative splicing events in both junction arrays and RNA-seq. Common results and discrepancies between both technologies were validated or resolved by more than 200 PCRs.
2018-09-05 | GSE104610 | GEO
Project description:Comparison of RNA-seq and Microarray Platforms for Splice Event Detection using a Cross-Platform Algorithm
| PRJNA414289 | ENA
Project description:In this study, we compare the performance of RNA-seq (Illumina HiSeq) and junction arrays (Affymetrix Human Transcriptome array) for the analysis of splicing events. Three different cell lines were treated with CX-4945, a drug that severely affects splicing. To make a fair comparison, we developed EventPointer, an algorithm that detects and labels alternative splicing events in both junction arrays and RNA-seq. Common results and discrepancies between both technologies were validated or resolved by more than 200 PCRs.
2018-09-05 | GSE104973 | GEO
Project description:Comparison of RNA-seq and Microarray Platforms for Splice Event Detection using a Cross-Platform Algorithm [RNA-Seq]
| PRJNA414291 | ENA
Project description:This SuperSeries is composed of the SubSeries listed below.
2018-09-05 | GSE104974 | GEO
Project description:Self-training algorithm for splice junction detection using RNA-seq and its application to honey bee transcriptomes
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Project description:BACKGROUND:RNA-seq is a reference technology for determining alternative splicing at genome-wide level. Exon arrays remain widely used for the analysis of gene expression, but show poor validation rate with regard to splicing events. Commercial arrays that include probes within exon junctions have been developed in order to overcome this problem. We compare the performance of RNA-seq (Illumina HiSeq) and junction arrays (Affymetrix Human Transcriptome array) for the analysis of transcript splicing events. Three different breast cancer cell lines were treated with CX-4945, a drug that severely affects splicing. To enable a direct comparison of the two platforms, we adapted EventPointer, an algorithm that detects and labels alternative splicing events using junction arrays, to work also on RNA-seq data. Common results and discrepancies between the technologies were validated and/or resolved by over 200 PCR experiments. RESULTS:As might be expected, RNA-seq appears superior in cases where the technologies disagree and is able to discover novel splicing events beyond the limitations of physical probe-sets. We observe a high degree of coherence between the two technologies, however, with correlation of EventPointer results over 0.90. Through decimation, the detection power of the junction arrays is equivalent to RNA-seq with up to 60 million reads. CONCLUSIONS:Our results suggest, therefore, that exon-junction arrays are a viable alternative to RNA-seq for detection of alternative splicing events when focusing on well-described transcriptional regions.
| S-EPMC6156849 | biostudies-literature
Project description:Aminoglycosides resistance mechanisms inference algorithm
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Project description:MudPIT datasets for NaOH-extracted and Salt-and-Detergent (SD)-extracted rat nuclear membranes were obtained from skeletal muscle and liver tissue as described in the following references:
Wilkie GS, Korfali N, Swanson SK, Malik P, Srsen V, Batrakou DG, de las Heras J, Zuleger N, Kerr AR, Florens L, Schirmer EC. Several novel nuclear envelope transmembrane proteins identified in skeletal muscle have cytoskeletal associations Mol Cell Proteomics 2011 Jan;10(1):M110003129
Korfali N, Wilkie GS, Swanson SK, Srsen V, de Las Heras J, Batrakou DG, Malik P, Zuleger N, Kerr AR, Florens L, Schirmer EC. The nuclear envelope proteome differs notably between tissues Nucleus 2012 Nov-Dec;3(6):552-64
The trypsin-digested MS datasets from these studies were searched again using ProLuCID against a database containing tissue-specific junction sequences as such:
We analyzed RNA-Seq data from five rat tissues (heart, skeletal muscle, liver, brain, and testes) produced by two separate research groups, hereby referred to as GSE4 (Yu, Y., J.C. Fuscoe, C. Zhao, C. Guo, M. Jia, T. Qing, et al., A rat RNA-Seq transcriptomic BodyMap across 11 organs and 4 developmental stages. Nat Commun, 2014; 5: 3230.) and GSE5 (Merkin, J., C. Russell, P. ChenC.B. Burge, Evolutionary dynamics of gene and isoform regulation in Mammalian tissues. Science, 2012; 338(6114): 1593-9.)
GSE4 has higher read coverage over junctions, but only one suitable sample per tissue while GSE5 has lower coverage but many replicates. Novel junctions identified in both datasets were considered to be high confidence. Differentially spliced transcripts were determined and quantified using Modeling Alternative Junction Inclusion Quantification (MAJIQ) software. Splice junctions rather than whole isoforms were quantified due to the known limitations in reconstructing whole transcripts from short read data. The software builds splice graphs from RNA-Seq reads spanning spliced junctions, incorporates un-annotated junctions, and uses information from replicate samples to build a Bayesian posterior distribution, outputting the expected percentage spliced in values (E|PSI|) corresponding to the percentage of transcripts that are expected to contain the given splice junction or in the case of a comparison, change in PSI (E|dPSI). In accordance with previous literature, we considered an alternative splicing event between tissues when E|dPSI greater than 0.2.
Tissue-specific junction sequence databases were generated for rat muscle and liver tissues. In each case the union of all splice junctions detected by STAR aligner for each replicate from GSE4 and GSE5 was taken. Junctions were filtered to remove junctions supported by less than 6 reads and junctions predicting an intron length of less than 60 nucleotides (a standard cut-off as there are very few smaller annotated junctions). Junction coordinates were extended by 66 nucleotides in both directions, and then translated in three frames according to the directionality of the gene. This produced peptide sequences of about 44 amino acids in length. Sequences were removed if the translation produced a stop codon before the junction based on standard practice. Novel exons and intron retentions predicted by MAJIQ were similarly translated in three frames and added to the database, but were removed if the translated sequence was less than 7 amino acids long. All novel and annotated junctions were combined with novel exons, intron retentions, and Ensembl rat protein database sequences to produce a final protein sequence database. Finally, coordinates of junction peptides were checked against the original fasta sequence to be sure that the peptide crossed the junction with a start less or equal to 22 amino acids away and an end greter or equal to 22 amino acids away.
2018-01-18 | MSV000081951 | MassIVE
Project description:Copy number variants (CNVs) are currently defined as genomic sequences that are polymorphic in copy number and range in length from 1,000 to several million base pairs. Among current array-based CNV detection platforms, long-oligonucleotide arrays promise the highest resolution. However, the performance of currently available analytical tools suffers when applied to these data because of the lower signal:noise ratio inherent in oligonucleotide-based hybridization assays. We have developed wuHMM, an algorithm for mapping CNVs from array comparative genomic hybridization (aCGH) platforms comprised of 385,000 to more than 3 million probes. wuHMM is unique in that it can utilize sequence divergence information to reduce the false positive rate (FPR). We apply wuHMM to 385K-aCGH, 2.1M-aCGH, and 3.1M-aCGH experiments comparing the 129X1/SvJ and C57BL/6J inbred mouse genomes. We assess wuHMM’s performance on the 385K platform by comparison to the higher resolution platforms and we independently validate 10 CNVs. The method requires no training data and is robust with respect to changes in algorithm parameters. At a FPR of less than 10%, the algorithm can detect CNVs with five probes on the 385K platform and three on the 2.1M and 3.1M platforms, resulting in effective resolutions of 24 kb, 2-5 kb, and 1 kb, respectively. Keywords: CNV detection algorithm development and assessment
2008-03-12 | GSE10511 | GEO