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Motivation: The fractional fetal DNA concentration is one of the critical parameters for non-invasive prenatal diagnosis based on the analysis of DNA in maternal plasma. Massively parallel sequencing (MPS) of DNA in maternal plasma has been demonstrated to be a powerful tool for the non-invasive prenatal diagnosis of fetal chromosomal aneuploidies. With the rapid advance of MPS technologies, the sequencing cost per base is dramatically reducing, especially when using targeted MPS. Even though several approaches have been developed for deducing the fractional fetal DNA concentration, none of them can be used to deduce the fractional fetal DNA concentration directly from the sequencing data without prior genotype information. Result: In this study, we implement a statistical mixture model, named FetalQuant, which utilizes the maximum likelihood to estimate the fractional fetal DNA concentration directly from targeted MPS of DNA in maternal plasma. This method allows the improved deduction of the fractional fetal DNA concentration, obviating the need of genotype information without loss of accuracy. Furthermore, by using Bayes’ rule, this method can distinguish the informative single-nucleotide polymorphism loci where the mother is homozygous and the fetus is heterozygous. We believe that FetalQuant can help expand the spectrum of diagnostic applications using MPS on DNA in maternal plasma. Availability: Software and simulation data are available at http://sourceforge.net/projects/fetalquant/ Contact: haosun@cuhk.edu.hk Supplementary Information: Supplementary data are available at Bioinformatics online.

Motivation The bisulfite sequencing technology has been widely used to study the DNA methylation profile in many species. However, most of the current visualization tools for bisulfite sequencing data only provide high-level views (i.e. overall methylation densities) while miss the methylation dynamics at nucleotide level. Meanwhile, they also focus on CpG sites while omit other information (such as genotypes on SNP sites) which could be helpful for interpreting the methylation pattern of the data. A bioinformatics tool that visualizes the methylation statuses at nucleotide level and preserves the most essential information of the sequencing data is thus valuable and needed. Results We have developed BSviewer, a lightweight nucleotide-level visualization tool for bisulfite sequencing data. Using an imprinting gene as an example, we show that BSviewer could be specifically helpful for interpreting the data with allele-specific DNA methylation pattern. Availability and implementation BSviewer is implemented in Perl and runs on most GNU/Linux platforms. Source code and testing dataset are freely available at http://sunlab.cpy.cuhk.edu.hk/BSviewer/.