Analysis of Exercise-Induced Periodic Breathing Using an Autoregressive Model and the Hilbert-Huang Transform.

Evaluation of exercise-induced periodic breathing (PB) in cardiopulmonary exercise testing (CPET) is one of important diagnostic evidences to judge the prognosis of chronic heart failure cases. In this study, we propose a method for the quantitative analysis of measured ventilation signals from an exercise test. We used an autoregressive (AR) model to filter the breath-by-breath measurements of ventilation from exercise tests. Then, the signals before reaching the most ventilation were decomposed into intrinsic mode functions (IMF) by using the Hilbert-Huang transform (HHT). An IMF represents a simple oscillatory pattern which catches a part of original ventilation signal in different frequency band. For each component of IMF, we computed the number of peaks as the feature of its oscillatory pattern denoted by Δ i . In our experiment, 61 chronic heart failure patients with or without PB pattern were studied. The computed peaks of the third and fourth IMF components, Δ3 and Δ4, were statistically significant for the two groups (both p values < 0.02). In summary, our study shows a close link between the HHT analysis and level of intrinsic energy for pulmonary ventilation. The third and fourth IMF components are highly potential to indicate the prognosis of chronic heart failure.

SeqEntropy: genome-wide assessment of repeats for short read sequencing.

BACKGROUND: Recent studies on genome assembly from short-read sequencing data reported the limitation of this technology to reconstruct the entire genome even at very high depth coverage. We investigated the limitation from the perspective of information theory to evaluate the effect of repeats on short-read genome assembly using idealized (error-free) reads at different lengths. METHODOLOGY/PRINCIPAL FINDINGS: We define a metric H(k) to be the entropy of sequencing reads at a read length k and use the relative loss of entropy ΔH(k) to measure the impact of repeats for the reconstruction of whole-genome from sequences of length k. In our experiments, we found that entropy loss correlates well with de-novo assembly coverage of a genome, and a score of ΔH(k)>1% indicates a severe loss in genome reconstruction fidelity. The minimal read lengths to achieve ΔH(k)<1% are different for various organisms and are independent of the genome size. For example, in order to meet the threshold of ΔH(k)<1%, a read length of 60 bp is needed for the sequencing of human genome (3.2 10(9) bp) and 320 bp for the sequencing of fruit fly (1.8×10(8) bp). We also calculated the ΔH(k) scores for 2725 prokaryotic chromosomes and plasmids at several read lengths. Our results indicate that the levels of repeats in different genomes are diverse and the entropy of sequencing reads provides a measurement for the repeat structures. CONCLUSIONS/SIGNIFICANCE: The proposed entropy-based measurement, which can be calculated in seconds to minutes in most cases, provides a rapid quantitative evaluation on the limitation of idealized short-read genome sequencing. Moreover, the calculation can be parallelized to scale up to large euakryotic genomes. This approach may be useful to tune the sequencing parameters to achieve better genome assemblies when a closely related genome is already available.

EBARDenovo: highly accurate de novo assembly of RNA-Seq with efficient chimera-detection.

MOTIVATION: High-accuracy de novo assembly of the short sequencing reads from RNA-Seq technology is very challenging. We introduce a de novo assembly algorithm, EBARDenovo, which stands for Extension, Bridging And Repeat-sensing Denovo. This algorithm uses an efficient chimera-detection function to abrogate the effect of aberrant chimeric reads in RNA-Seq data. RESULTS: EBARDenovo resolves the complications of RNA-Seq assembly arising from sequencing errors, repetitive sequences and aberrant chimeric amplicons. In a series of assembly experiments, our algorithm is the most accurate among the examined programs, including de Bruijn graph assemblers, Trinity and Oases. AVAILABILITY AND IMPLEMENTATION: EBARDenovo is available at http://ebardenovo.sourceforge.net/. This software package (with patent pending) is free of charge for academic use only. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Quantitative assessment of mitochondrial DNA copies from whole genome sequencing.

BACKGROUND: Mitochondrial dysfunction is associated with various aging diseases. The copy number of mtDNA in human cells may therefore be a potential biomarker for diagnostics of aging. Here we propose a new computational method for the accurate assessment of mtDNA copies from whole genome sequencing data. RESULTS: Two families of the human whole genome sequencing datasets from the HapMap and the 1000 Genomes projects were used for the accurate counting of mitochondrial DNA copy numbers. The results revealed the parental mitochondrial DNA copy numbers are significantly lower than that of their children in these samples. There are 8%~21% more copies of mtDNA in samples from the children than from their parents. The experiment demonstrated the possible correlations between the quantity of mitochondrial DNA and aging-related diseases. CONCLUSIONS: Since the next-generation sequencing technology strives to deliver affordable and non-biased sequencing results, accurate assessment of mtDNA copy numbers can be achieved effectively from the output of whole genome sequencing. We implemented the method as a software package MitoCounter with the source code and user's guide available to the public at http://sourceforge.net/projects/mitocounter/.

A gene expression profile for vascular invasion can predict the recurrence after resection of hepatocellular carcinoma: a microarray approach.

BACKGROUND: Recurrence after hepatocellular carcinoma (HCC) resection is the major obstacle to improved survival. The presence of vascular invasion (VI) in pathology specimens is a well-known unfavorable prognostic factor for HCC recurrence. Though some VI-related genes have been reported, their association with recurrence-free survival is not known. We hypothesized that a gene expression profile for VI can predict the recurrence of HCC after liver resection. METHODS: Eighteen patients receiving complete HCC resection were included as a "training group". Genome-wide gene expression profile was obtained for each tumor using a microarray technique. Datasets were subjected to clustering analysis supervised by the presence or absence of VI to obtain 14 discriminative genes. We then applied those genes to execute pattern recognition using the k-Nearest Neighbor (KNN) classification method, and the best model for this VI gene signature to predict recurrence-free survival in the training group was obtained. The resulting model was then tested in an independent "test group" of 35 patients. RESULTS: A 14-gene profile was extracted which could accurately separate ten patients with VI and eight patients without VI in the "training group". In the "test group", significant difference in disease-free survival was found between patients predicted to have and not to have recurrence (P = .02823). In patients with stage_I disease, this model can also predict outcomes (P = .000205). CONCLUSIONS: Using the 14-gene expression profile extracted from microarrays based on the presence of VI can effectively predict recurrence after HCC resection. This approach might facilitate "personalized medicine" for HCC patients after surgical resection.

Integrated minimum-set primers and unique probe design algorithms for differential detection on symptom-related pathogens.

MOTIVATION: Differential detection on symptom-related pathogens (SRP) is critical for fast identification and accurate control against epidemic diseases. Conventional polymerase chain reaction (PCR) requires a large number of unique primers to amplify selected SRP target sequences. With multiple-use primers (mu-primers), multiple targets can be amplified and detected in one PCR experiment under standard reaction condition and reduced detection complexity. However, the time complexity of designing mu-primers with the best heuristic method available is too vast. We have formulated minimum-set mu-primer design problem as a set covering problem (SCP), and used modified compact genetic algorithm (MCGA) to solve this problem optimally and efficiently. We have also proposed new strategies of primer/probe design algorithm (PDA) on combining both minimum-set (MS) mu-primers and unique (UniQ) probes. Designed primer/probe set by PDA-MS/UniQ can amplify multiple genes simultaneously upon physical presence with minimum-set mu-primer amplification (MMA) before intended differential detection with probes-array hybridization (PAH) on the selected target set of SRP. RESULTS: The proposed PDA-MS/UniQ method pursues a much smaller number of primers set compared with conventional PCR. In the simulation experiment for amplifying 12 669 target sequences, the performance of our method with 68% reduction on required mu-primers number seems to be superior to the compared heuristic approaches in both computation efficiency and reduction percentage. Our integrated PDA-MS/UniQ method is applied to the differential detection on 9 plant viruses from 4 genera with MMA and PAH of 11 mu-primers instead of 18 unique ones in conventional PCR while amplifying overall 9 target sequences. The results of wet lab experiments with integrated MMA-PAH system have successfully validated the specificity and sensitivity of the primers/probes designed with our integrated PDA-MS/UniQ method.