An important prerequisite for such discoveries are computational tools that are able to rapidly and accurately compare large datasets generated from complex bacterial communities to identify features that distinguish them. We present a statistical method for comparing clinical metagenomic samples from two treatment populations on the basis of count data ( e. g. as obtained through sequencing) to detect differentially abundant features. Our method, Metastats, employs the false discovery rate to improve specificity in high-complexity environments, and separately handles sparsely-sampled features using Fisher’s exact test. Under a variety of simulations, we show that Metastats performs

well compared to previously used methods, and significantly outperforms other methods for features with sparse counts. We demonstrate the utility of our method on several datasets including a 16S 4-Hydroxytamoxifen rRNA survey of obese and lean human gut microbiomes, COG functional profiles of infant and mature gut microbiomes, and bacterial and viral metabolic subsystem data inferred from random

sequencing of 85 metagenomes. The application of our method to the obesity Selleckchem Acalabrutinib dataset reveals differences between obese and lean subjects not reported in the original study. For the COG and subsystem datasets, we provide the first statistically rigorous assessment of the differences between these populations. GSK2879552 inhibitor The methods described in this paper are the first to address clinical metagenomic datasets comprising samples from multiple subjects. Our methods are robust across datasets of varied complexity and sampling level. While designed for metagenomic applications, our software can also be applied to digital gene expression studies ( e. g. SAGE). A web server implementation of our methods and freely available source code can be found at http://metastats.cbcb.umd.edu/.”
“Polyaniline (PANI) was synthesized by the well-known oxidative polymerization of aniline with ammonium peroxodisulfate as the oxidant. The morphological, structural, thermal, optical, magnetic, and electrical properties were characterized with scanning

electron microscopy, X-ray diffraction, Fourier transform infrared, thermogravimetric analysis, differential scanning calorimetry, ultraviolet-visible spectroscopy, room-tempera tu re magnetic measurements, and low-temperature electrical transport measurements by the standard four-probe method. Greater thermal stability and crystallinity were observed in doped PANI versus pure PANI. Magnetic measurements showed that the magnetic susceptibility was field-dependent. Positive and negative susceptibility values were observed. This may have been due to the interactions of magnetic ions among interchains or intrachains of the polymer matrix. The alternating-current (ac) conductivity was measured in the temperature range of 77-300 K in the frequency range of 20 Hz to 1 MHz.