MOTIVATION: Next-generation sequencing captures sequence differences in reads relative to a reference genome or transcriptome, including splicing events and complex variants involving multiple mismatches and long indels. We present computational methods for fast detection of complex variants and splicing in short reads, based on a successively constrained search process of merging and filtering position lists from a genomic index. Our methods are implemented in GSNAP (Genomic Short-read Nucleotide Alignment Program), which can align both single- and paired-end reads as short as 14 nt and of arbitrarily long length. It can detect short- and long-distance splicing, including interchromosomal splicing, in individual reads, using probabilistic models or a database of known splice sites. Our program also permits SNP-tolerant alignment to a reference space of all possible combinations of major and minor alleles, and can align reads from bisulfite-treated DNA for the study of methylation state. RESULTS: In comparison testing, GSNAP has speeds comparable to existing programs, especially in reads of > or=70 nt and is fastest in detecting complex variants with four or more mismatches or insertions of 1-9 nt and deletions of 1-30 nt. Although SNP tolerance does not increase alignment yield substantially, it affects alignment results in 7-8% of transcriptional reads, typically by revealing alternate genomic mappings for a read. Simulations of bisulfite-converted DNA show a decrease in identifying genomic positions uniquely in 6% of 36 nt reads and 3% of 70 nt reads. AVAILABILITY: Source code in C and utility programs in Perl are freely available for download as part of the GMAP package at http://share.gene.com/gmap.

UNLABELLED: We address the problem of using expression data and prior biological knowledge to identify differentially expressed pathways or groups of genes. Following an idea of Ideker et al. (2002), we construct a gene interaction network and search for high-scoring subnetworks. We make several improvements in terms of scoring functions and algorithms, resulting in higher speed and accuracy and easier biological interpretation. We also assign significance levels to our results, adjusted for multiple testing. Our methods are successfully applied to three human microarray data sets, related to cancer and the immune system, retrieving several known and potential pathways. The method, denoted by the acronym GXNA (Gene eXpression Network Analysis) is implemented in software that is publicly available and can be used on virtually any microarray data set. SUPPLEMENTARY INFORMATION: The source code and executable for the software, as well as certain supplemental materials, can be downloaded from http://stat.stanford.edu/~serban/gxna.

Channel uncertainty limits the achievable data rates of certain ultra-wideband systems due to the need to estimate the channel. The use of bursty duty-cycled transmission reduces the channel uncertainty because the receiver has to estimate the channel only when transmission takes place, but the maximum amount of burstiness and hence the possible reduction of channel uncertainty both depend on the spectral efficiency of the modulation scheme used. This general principle is demonstrated by comparing the channel conditions that allow duty-cycled direct-sequence spread spectrum (DSSS) and pulse position modulation (PPM) to achieve the additive white Gaussian noise (AWGN) channel capacity in the wideband limit. We show that duty-cycled DSSS systems achieve the wideband capacity as long as the number of independently faded resolvable paths increasessublinearlywith the bandwidth, while duty-cycled PPM systems can achieve the wideband capacity only if the number of paths increasessublogarithmically. The difference is due to the fact that DSSS is spectrally more efficient than PPM and hence allows more bursty transmission.