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Finding Novel Transcripts in High-Resolution Genome-Wide Microarray Data Using the GenRate Model
- In RECOMB
"... Abstract. Genome-wide microarray designs containing millions to tens of millions of probes will soon become available for a variety of mammals, including mouse and human. These “tiling arrays ” can potentially lead to significant advances in science and medicine, e.g., by indicating new genes and al ..."
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Abstract. Genome-wide microarray designs containing millions to tens of millions of probes will soon become available for a variety of mammals, including mouse and human. These “tiling arrays ” can potentially lead to significant advances in science and medicine, e.g., by indicating new genes and alternative primary and secondary transcripts. While bottomup pattern matching techniques (e.g., hierarchical clustering) can be used to find gene structures in tiling data, we believe the many interacting hidden variables and complex noise patterns more naturally lead to an analysis based on generative models. We describe a generative model of tiling data and show how the iterative sum-product algorithm can be used to infer hybridization noise, probe sensitivity, new transcripts and alternative transcripts. We apply our method, called GenRate, to a new exon tiling data set from mouse chromosome 4 and show that it makes significantly more predictions than a previously described hierarchical clustering method at the same false positive rate. GenRate correctly predicts many known genes, and also predicts new gene structures. As new problems arise, additional hidden variables can be incorporated into the model in a principled fashion, so we believe that GenRate will prove to be a useful tool in the new era of genome-wide tiling microarray analysis. 1
Time Slot Groups -- A Data Structure for QoS-Constrained Advance Bandwidth Reservation and Admission Control
, 2008
"... In this paper we present Time Slot Groups (TSG), a novel, efficient data structure for QoS-constrained advance bandwidth reservation and admission control. The data structure divides the time horizon into T equally sized time slots and can be used for serving efficiently complex bandwidth reservat ..."
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Cited by 2 (2 self)
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In this paper we present Time Slot Groups (TSG), a novel, efficient data structure for QoS-constrained advance bandwidth reservation and admission control. The data structure divides the time horizon into T equally sized time slots and can be used for serving efficiently complex bandwidth reservation requests specifying the duration of the reservation, the minimum required bandwidth, the earliest possible starting time and the latest possible finish time. The data structure supports reservation queries in time O(k+(T/k)·log(k)) and reservation updates in time O(k+(T/k)), where k is a user-defined parameter.
Custom Design and Analysis of High-Density Oligonucleotide Bacterial Tiling Microarrays
- HAFEMEISTER ET AL.: SELECTING OLIGONUCLEOTIDE PROBES FOR WHOLE-GENOME TILING ARRAYS WITH A CROSS-HYBRIDIZATION... 1651
, 2009
"... Background: High-density tiling microarrays are a powerful tool for the characterization of complete genomes. The two major computational challenges associated with custom-made arrays are design and analysis. Firstly, several genome dependent variables, such as the genome’s complexity and sequence c ..."
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Background: High-density tiling microarrays are a powerful tool for the characterization of complete genomes. The two major computational challenges associated with custom-made arrays are design and analysis. Firstly, several genome dependent variables, such as the genome’s complexity and sequence composition, need to be considered in the design to ensure a high quality microarray. Secondly, since tiling projects today very often exceed the limits of conventional array-experiments, researchers cannot use established computer tools designed for commercial arrays, and instead have to redesign previous methods or create novel tools. Principal Findings: Here we describe the multiple aspects involved in the design of tiling arrays for transcriptome analysis and detail the normalisation and analysis procedures for such microarrays. We introduce a novel design method to make two 280,000 feature microarrays covering the entire genome of the bacterial species Escherichia coli and Neisseria meningitidis, respectively, as well as the use of multiple copies of control probe-sets on tiling microarrays. Furthermore, a novel normalisation and background estimation procedure for tiling arrays is presented along with a method for array analysis focused on detection of short transcripts. The design, normalisation and analysis methods have been applied in various experiments and several of the detected novel short transcripts have been biologically confirmed by Northern blot tests. Conclusions: Tiling-arrays are becoming increasingly applicable in genomic research, but researchers still lack both the tools
Genrate: A generative model that reveals novel transcripts in genome-tiling microarray data
- Journal of Computational Biology
"... Genome-wide microarray designs containing millions to hundreds of millions of probes are available for a variety of mammals, including mouse and human. These genome tiling arrays can potentially lead to significant advances in science and medicine, e.g., by indicating new genes and alternative prima ..."
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Cited by 1 (0 self)
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Genome-wide microarray designs containing millions to hundreds of millions of probes are available for a variety of mammals, including mouse and human. These genome tiling arrays can potentially lead to significant advances in science and medicine, e.g., by indicating new genes and alternative primary and secondary transcripts. While bottom-up pattern matching techniques (e.g., hierarchical clustering) can be used to find gene structures in microarray data, we believe the many interacting hidden variables and complex noise patterns more naturally lead to an analysis based on generative models. We describe a generative model of tiling data and show how the sum-product algorithm can be used to infer hybridization noise, probe sensitivity, new transcripts, and alternative transcripts. The method, called GenRate, maximizes a global scoring function that enables multiple transcripts to compete for ownership of putative probes. We apply GenRate to a new exon tiling dataset from mouse chromosome 4 and show that it makes significantly more predictions than a previously described hierarchical clustering method at the same false positive rate. GenRate correctly predicts many known genes and also predicts new gene structures. As new problems arise, additional hidden variables can be incorporated into the model in a principled fashion, so we believe that GenRate will prove to be a useful tool in the new era of genome-wide tiling microarray analysis. Key words: exon microarrays, whole-genome tiling microarrays, transcripts, gene variants, alternative splicing, generative models, factor graphs, sum-product algorithm.
The transcriptional activity of human
"... A DNA microarray representing nearly all of the unique sequences of human Chromosome 22 was constructed and used to measure global-transcriptional activity in placental poly(A)+ RNA. We found that many of the known, related and predicted genes are expressed. More importantly, our study reveals twice ..."
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A DNA microarray representing nearly all of the unique sequences of human Chromosome 22 was constructed and used to measure global-transcriptional activity in placental poly(A)+ RNA. We found that many of the known, related and predicted genes are expressed. More importantly, our study reveals twice as many transcribed bases as have been reported previously. Many of the newly discovered expressed fragments were verified by RNA blot analysis and a novel technique called differential hybridization mapping (DHM). Interestingly, a significant fraction of these novel fragments are expressed antisense to previously annotated introns. The coding potential of these novel expressed regions is supported by their sequence conservation in the mouse genome. This study has greatly increased our understanding of the biological information encoded on a human chromosome. To facilitate the dissemination of these results to the scientific community, we have developed a comprehensive Web resource to present the findings of this study and other features of human Chromosome 22 at
