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1.  Blind spots of quantitative RNA-seq: the limits for assessing abundance, differential expression, and isoform switching 
BMC Bioinformatics  2013;14:370.
Background
RNA-seq is now widely used to quantitatively assess gene expression, expression differences and isoform switching, and promises to deliver results for the entire transcriptome. However, whether the transcriptional state of a gene can be captured accurately depends critically on library preparation, read alignment, expression estimation and the tests for differential expression and isoform switching. There are comparisons available for the individual steps but there is not yet a systematic investigation which specific genes are impacted by biases throughout the entire analysis workflow. It is especially unclear whether for a given gene, with current methods and protocols, expression changes and isoform switches can be detected.
Results
For the human genes, we report their detectability under various conditions using different approaches. Overall, we find that the input material has the biggest influence and may, depending on the protocol and RNA degradation, exhibit already strong length-dependent over- and underrepresentation of transcripts. The alignment step aligns for 50% of the isoforms up to 99% of the reads correctly; only in the presence of transcript modifications mainly short isoforms will have a low alignment rate. In our dataset, we found that, depending on the aligner and the input material used, the expression estimation of up to 93% of the genes being accurate within a factor of two; with the deviations being due to ambiguous alignments. Detection of differential expression using a negative-binomial count model works reliably for our simulated data but is dependent on the count accuracy. Interestingly, using the fold-change instead of the p-value as a score for differential expression yields the same performance in the situation of three replicates and the true change being two-fold. Isoform switching is harder to detect and for at least 109 genes the isoform differences evade detection independent of the method used.
Conclusions
RNA-seq is a reliable tool but the repetitive nature of the human genome makes the origin of the reads ambiguous and limits the detectability for certain genes. RNA-seq does not equally well represent isoforms independent of their size which may range from ~200nt to ~100′000nt. Researchers are advised to verify that their target genes do not have extreme properties with respect to repeated regions, GC content, and isoform length and complexity.
doi:10.1186/1471-2105-14-370
PMCID: PMC3879183  PMID: 24365034
2.  JASPAR 2014: an extensively expanded and updated open-access database of transcription factor binding profiles 
Nucleic Acids Research  2013;42(D1):D142-D147.
JASPAR (http://jaspar.genereg.net) is the largest open-access database of matrix-based nucleotide profiles describing the binding preference of transcription factors from multiple species. The fifth major release greatly expands the heart of JASPAR—the JASPAR CORE subcollection, which contains curated, non-redundant profiles—with 135 new curated profiles (74 in vertebrates, 8 in Drosophila melanogaster, 10 in Caenorhabditis elegans and 43 in Arabidopsis thaliana; a 30% increase in total) and 43 older updated profiles (36 in vertebrates, 3 in D. melanogaster and 4 in A. thaliana; a 9% update in total). The new and updated profiles are mainly derived from published chromatin immunoprecipitation-seq experimental datasets. In addition, the web interface has been enhanced with advanced capabilities in browsing, searching and subsetting. Finally, the new JASPAR release is accompanied by a new BioPython package, a new R tool package and a new R/Bioconductor data package to facilitate access for both manual and automated methods.
doi:10.1093/nar/gkt997
PMCID: PMC3965086  PMID: 24194598
3.  Elevated blood pressure and analgesic overuse in chronic daily headache: an outpatient clinic-based study from China 
Background
Many studies have reported that hypertension is common in chronic daily headache (CDH) and its subtype chronic migraine (CM), but the reason is still poorly understood. Our clinical literature review suggested that analgesic overuse may be associated with elevated blood pressure (BP), so we performed the present study to investigate the frequency of elevated BP and its link with analgesic overuse in CDH and its subtypes.
Methods
A cross-sectional study was conducted in neurology outpatients with a diagnosis of CDH according to International Headache Society criteria. CDH patients were classified into CM and non-CM groups, and subclassified with or without analgesic overuse.
Results
Elevated BP was present in 27.96% of CDH patients. Compared with non-CM patients, patients with CM had a longer duration of headache and more severe pain intensity, and a family history of headache and analgesic overuse were also more common, but the elevated BP frequency was not different between the two groups. Almost one-third of the patients had analgesic overuse; 96.8% of which comprised acetaminophen-containing agents. Those with analgesic overuse had a higher frequency of headache than those without analgesic overuse in both the CM and non-CM groups.
Conclusions
Although the CM patients had a longer duration of headache, more severe intensity, the frequency of elevated BP wasn’t higher than non-CM group. Analgesic overuses maybe the reason of higher frequency of elevated BP in CDH and its subtypes. This may have predictive value for clinicians to improve CDH management.
doi:10.1186/1129-2377-14-51
PMCID: PMC3691651  PMID: 23773858
Acetaminophen; Analgesic overuse; Chronic daily headache; Elevated blood pressure
4.  Prevalence and risk factors for depression and anxiety among outpatient migraineurs in mainland China 
The Journal of Headache and Pain  2012;13(4):303-310.
This study aimed to investigate the prevalence and risk factors for anxiety and depression symptoms in outpatient migraineurs in mainland China. In addition, we evaluated whether the Hospital Anxiety and Depression Scale (HADS) provided sufficient validity to screen depression and anxiety. A cross-sectional study was conducted consecutively at our headache clinic. Migraine was diagnosed according to International Classification of Headache Disorders, 2nd edition (ICHD-II). Demographic characteristics and clinical features were collected by headache questionnaire. Anxiety and depression symptoms about migraineurs were assessed using HADS. Several questionnaires were simultaneously used to evaluate patients with depressive disorder including the Hamilton Depression Rating Scale-17 (HAMD), Hamilton Anxiety Rating Scale (HAMA) and HADS. Pearson correlation analysis was applied to test the validity of HADS. 176 outpatients with migraine (81.8 % female) were included. Overall, 17.6 and 38.1 % participants had depression and anxiety, respectively. Possible risk factors for depression in migraineurs included headache intensity of first onset of migraine, migraine with presymptom, migraine with family history and migraine disability. The possible risk factors for anxiety included fixed attack time of headache in one day and poor sleeping, and age represented a protective factor for anxiety. The correlation coefficient of HADS-A and HADS-D with HAMA and HAMD was 0.666 and 0.508, respectively (P < 0.01). This study demonstrates that depression and anxiety comorbidity in our mainland Chinese migraineurs are also common, and several risk factors were identified that may provide predictive value. These findings can help clinicians to identify and treat anxiety and depression in order to improve migraine management.
doi:10.1007/s10194-012-0442-9
PMCID: PMC3356469  PMID: 22466285
Anxiety; Cross-sectional study; Depression; Migraine; Risk factor
5.  Classification and clinical features of headache patients: an outpatient clinic study from China 
The Journal of Headache and Pain  2011;12(5):561-567.
This study aimed to analyze and classify the clinical features of headache in neurological outpatients. A cross-sectional study was conducted consecutively from March to May 2010 for headache among general neurological outpatients attending the First Affiliated Hospital of Chongqing Medical University. Personal interviews were carried out and a questionnaire was used to collect medical records. Diagnosis of headache was according to the International classification of headache disorders, 2nd edition (ICHD-II). Headache patients accounted for 19.5% of the general neurology clinic outpatients. A total of 843 (50.1%) patients were defined as having primary headache, 454 (27%) secondary headache, and 386 (23%) headache not otherwise specified (headache NOS). For primary headache, 401 (23.8%) had migraine, 399 (23.7%) tension-type headache (TTH), 8 (0.5%) cluster headache and 35 (2.1%) other headache types. Overall, migraine patients suffered (1) more severe headache intensity, (2) longer than 6 years of headache history and (3) more common analgesic medications use than TTH ones (p < 0.001).TTH patients had more frequent episodes of headaches than migraine patients, and typically headache frequency exceeded 15 days/month (p < 0.001); 22.8% of primary headache patients were defined as chronic daily headache. Almost 20% of outpatient visits to the general neurology department were of headache patients, predominantly primary headache of migraine and TTH. In outpatient headaches, more attention should be given to headache intensity and duration of headache history for migraine patients, while more attention to headache frequency should be given for the TTH ones.
doi:10.1007/s10194-011-0360-2
PMCID: PMC3173628  PMID: 21744226
Outpatient; Headache; Cross-sectional study; Clinical feature; Migraine
6.  Classification and clinical features of headache patients: an outpatient clinic study from China 
The Journal of Headache and Pain  2011;12(5):561-567.
This study aimed to analyze and classify the clinical features of headache in neurological outpatients. A cross-sectional study was conducted consecutively from March to May 2010 for headache among general neurological outpatients attending the First Affiliated Hospital of Chongqing Medical University. Personal interviews were carried out and a questionnaire was used to collect medical records. Diagnosis of headache was according to the International classification of headache disorders, 2nd edition (ICHD-II). Headache patients accounted for 19.5% of the general neurology clinic outpatients. A total of 843 (50.1%) patients were defined as having primary headache, 454 (27%) secondary headache, and 386 (23%) headache not otherwise specified (headache NOS). For primary headache, 401 (23.8%) had migraine, 399 (23.7%) tension-type headache (TTH), 8 (0.5%) cluster headache and 35 (2.1%) other headache types. Overall, migraine patients suffered (1) more severe headache intensity, (2) longer than 6 years of headache history and (3) more common analgesic medications use than TTH ones (p < 0.001).TTH patients had more frequent episodes of headaches than migraine patients, and typically headache frequency exceeded 15 days/month (p < 0.001); 22.8% of primary headache patients were defined as chronic daily headache. Almost 20% of outpatient visits to the general neurology department were of headache patients, predominantly primary headache of migraine and TTH. In outpatient headaches, more attention should be given to headache intensity and duration of headache history for migraine patients, while more attention to headache frequency should be given for the TTH ones.
doi:10.1007/s10194-011-0360-2
PMCID: PMC3173628  PMID: 21744226
Outpatient; Headache; Cross-sectional study; Clinical feature; Migraine
7.  Computational inference and analysis of genetic regulatory networks via a supervised combinatorial-optimization pattern 
BMC Systems Biology  2010;4(Suppl 2):S3.
Background
Post-genome era brings about diverse categories of omics data. Inference and analysis of genetic regulatory networks act prominently in extracting inherent mechanisms, discovering and interpreting the related biological nature and living principles beneath mazy phenomena, and eventually promoting the well-beings of humankind.
Results
A supervised combinatorial-optimization pattern based on information and signal-processing theories is introduced into the inference and analysis of genetic regulatory networks. An associativity measure is proposed to define the regulatory strength/connectivity, and a phase-shift metric determines regulatory directions among components of the reconstructed networks. Thus, it solves the undirected regulatory problems arising from most of current linear/nonlinear relevance methods. In case of computational and topological redundancy, we constrain the classified group size of pair candidates within a multiobjective combinatorial optimization (MOCO) pattern.
Conclusions
We testify the proposed approach on two real-world microarray datasets of different statistical characteristics. Thus, we reveal the inherent design mechanisms for genetic networks by quantitative means, facilitating further theoretic analysis and experimental design with diverse research purposes. Qualitative comparisons with other methods and certain related focuses needing further work are illustrated within the discussion section.
doi:10.1186/1752-0509-4-S2-S3
PMCID: PMC2982690  PMID: 20840730

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