SinicView: A visualization environment for comparisons of multiple nucleotide sequence alignment tools

BACKGROUND: Deluged by the rate and complexity of completed genomic sequences, the need to align longer sequences becomes more urgent, and many more tools have thus been developed. In the initial stage of genomic sequence analysis, a biologist is usually faced with the questions of how to choose the best tool to align sequences of interest and how to analyze and visualize the alignment results, and then with the question of whether poorly aligned regions produced by the tool are indeed not homologous or are just results due to inappropriate alignment tools or scoring systems used. Although several systematic evaluations of multiple sequence alignment (MSA) programs have been proposed, they may not provide a standard-bearer for most biologists because those poorly aligned regions in these evaluations are never discussed. Thus, a tool that allows cross comparison of the alignment results obtained by different tools simultaneously could help a biologist evaluate their correctness and accuracy. RESULTS: In this paper, we present a versatile alignment visualization system, called SinicView, (for Sequence-aligning INnovative and Interactive Comparison VIEWer), which allows the user to efficiently compare and evaluate assorted nucleotide alignment results obtained by different tools. SinicView calculates similarity of the alignment outputs under a fixed window using the sum-of-pairs method and provides scoring profiles of each set of aligned sequences. The user can visually compare alignment results either in graphic scoring profiles or in plain text format of the aligned nucleotides along with the annotations information. We illustrate the capabilities of our visualization system by comparing alignment results obtained by MLAGAN, MAVID, and MULTIZ, respectively. CONCLUSION: With SinicView, users can use their own data sequences to compare various alignment tools or scoring systems and select the most suitable one to perform alignment in the initial stage of sequence analysis

Impaired Prefronto-Thalamic Functional Connectivity as a Key Feature of Treatment-Resistant Depression: A Combined MEG, PET and rTMS Study

<div><p>Prefrontal left-right functional imbalance and disrupted prefronto-thalamic circuitry are plausible mechanisms for treatment-resistant depression (TRD). Add-on repetitive transcranial magnetic stimulation (rTMS), effective in treating antidepressant-refractory TRD, was administered to verify the core mechanisms underlying the refractoriness to antidepressants. Thirty TRD patients received a 2-week course of 10-Hz rTMS to the left dorsolateral prefrontal cortex (DLPFC). Depression scores were evaluated at baseline (W0), and the ends of weeks 1, 2, and 14 (W14). Responders were defined as those who showed an objective improvement in depression scores ≥50% after rTMS. Left-right frontal alpha asymmetry (FAA) was measured by magnetoencephalography at each time point as a proxy for left-right functional imbalance. Prefronto-thalamic connections at W0 and W14 were assessed by studying couplings between prefrontal alpha waves and thalamic glucose metabolism (PWTMC, reflecting intact thalamo-prefrontal connectivity). A group of healthy control subjects received magnetoencephalography at W0 (N = 50) to study whether FAA could have a diagnostic value for TRD, or received both magnetoencephalography and positron-emission-tomography at W0 (N = 10) to confirm the existence of PWTMC in the depression-free state. We found that FAA changes cannot differentiate between TRD and healthy subjects or between responders and non-responders. No PWTMC were found in the TRD group at W0, whereas restitution of the PWTMC was demonstrated only in the sustained responders at W14 and euthymic healthy controls. In conclusion, we affirmed impaired prefronto-thalamic functional connections, but not frontal functional imbalance, as a core deficit in TRD.</p></div

Demographic data and clinical variables between rTMS responders and non-responders.

<p>Note: MDE, major depressive episode; HDRS-17, 17-item Hamilton depression rating scales; BDI, Beck depression index; <b>^#</b> Significant decreases (pair-<i>t</i> test, p<0.05) as compared to baseline values; *p<0.05, **p<0.005.</p

Selection of frontal sensors (all colored squares).

<p>Green: left frontal sensors; Orange: right frontal sensors.</p

rTMS-related metabolic change in responders (<i>3-month vs. baseline</i>).

<p>Responders demonstrated significantly decreased metabolism in the thalamus, midbrain, cerebellum, posterior cingulate cortex (PCC), basal ganglia, occipital cortex, parahippocampus and subgenual anterior cingulate cortex (sgACC). Contrast bar denotes <i>t</i> values. The significance was set at a cluster-level corrected P<0.001 by paired-<i>t</i> tests.</p

Correlations between MEG frontal alpha activity and PET glucose metabolism in healthy controls and in depression before and after successful rTMS treatment.

<p>(A) <i>In healthy subjects</i>. Frontal alpha activity correlated well with glucose metabolism in the thalamus (circled in yellow). (B) <i>Before rTMS.</i> Frontal alpha activity correlated well with glucose metabolism in various parts of the prefrontal cortex, but did not correlate with thalamic activity. (C) <i>After successful rTMS treatment</i>. Frontal alpha activity correlated well with glucose metabolism in the thalamus (circled in yellow), brainstem, precuneus, and cingulate cortices. mPFC, medial prefrontal cortex; dACC, dorsal anterior cingulate cortex; MCC, middle cingulate cortex; SMA, supplementary motor area. Brain regions showing significant negative correlations (cluster-level corrected P<0.001) in each condition are shown in red color.</p

rTMS’s cumulative effects on reversing frontal alpha asymmetry (FAA).

<p>FAA of rTMS responders (in red color) and non-responders (in blue color) showed no difference from baseline (W0) to the end of the 1^st week (W1) and the 2^nd week (W2) after initiation of rTMS. In both groups, rTMS decreased FAA in a dose-dependent manner from W0 to W2, despite lack of statistical significance. During the follow-up period from the end of W2 to the 14^th week (W14), no active rTMS was used, and we observed a gradual rebound of FAA to its baseline value in both groups.</p