Preprocessing and Storing High-Throughput Sequencing Data

PathoQC: Computationally Efficient Read Preprocessing and Quality Control for High-Throughput Sequencing Data Sets

Quality control and read preprocessing are critical steps in the analysis of data sets generated from high-throughput genomic screens. In the most extreme cases, improper preprocessing can negatively affect downstream analyses and may lead to incorrect biological conclusions. Here, we present PathoQC, a streamlined toolkit that seamlessly combines the benefits of several popular quality control...

Preprocessing and Biclustering of High-throughput Expression Data

Compression of Structured High-Throughput Sequencing Data

Large biological datasets are being produced at a rapid pace and create substantial storage challenges, particularly in the domain of high-throughput sequencing (HTS). Most approaches currently used to store HTS data are either unable to quickly adapt to the requirements of new sequencing or analysis methods (because they do not support schema evolution), or fail to provide state of the art com...

Characterizing Transcriptomes from High-Throughput Sequencing Data

The DNA in our cells contains our genetic hereditary information, and is literally the blueprint of our body. The functional units of the genome are regions of continuous DNA sequence, and are called genes. According to the Central Dogma of Biology, the DNA sequence of the gene is transcribed into a messenger RNA (mRNA), which is in turn translated to proteins, which perform most tasks in the c...

Tools for mapping high-throughput sequencing data

MOTIVATION A ubiquitous and fundamental step in high-throughput sequencing analysis is the alignment (mapping) of the generated reads to a reference sequence. To accomplish this task, numerous software tools have been proposed. Determining the mappers that are most suitable for a specific application is not trivial. RESULTS This survey focuses on classifying mappers through a wide number of c...