High-throughput sequencing (HTS) data are commonly stored as raw sequencing reads in FASTQ format or as reads mapped to a reference, in SAM format, both with large memory footprints. Worldwide growth of HTS data has prompted the development of compression methods that aim to significantly reduce HTS data size. Here we report on a benchmarking study of available compression methods on a comprehensive set of HTS data using an automated framework.
In this paper, we compare the video codecs AV1 (version 1.0.0-2242 from August 2019), HEVC (HM and x265), AVC (x264), the exploration software JEM which is based on HEVC, and the VVC (successor of HEVC) test model VTM (version 4.0 from February 2019) under two fair and balanced configurations: All Intra for the assessment of intra coding and Maximum Coding Efficiency with all codecs being tuned for their best coding efficiency settings. VTM achieves the highest coding efficiency in both configurations, followed by JEM and AV1. The worst coding efficiency is achieved by x264 and x265, even in the placebo preset for highest coding efficiency. AV1 gained a lot in terms of coding efficiency compared to previous versions and now outperforms HM by 24% BD-Rate gains. VTM gains 5% over AV1 in terms of BD-Rates. By reporting separate numbers for JVET and AOM test sequences, it is ensured that no bias in the test sequences exists. When comparing only intra coding tools, it is observed that the complexity increases exponentially for linearly increasing coding efficiency.
Supplementary data are available at Bioinformatics online.
This paper provides the specification and an initial validation of an evaluation framework for the comparison of lossy compressors of genome sequencing quality values. The goal is to define reference data, test sets, tools and metrics that shall be used to evaluate the impact of lossy compression of quality values on human genome variant calling. The functionality of the framework is validated referring to two state-of-the-art genomic compressors. This work has been spurred by the current activity within the ISO/IEC SC29/WG11 technical committee (a.k.a. MPEG), which is investigating the possibility of starting a standardization activity for genomic information representation.
Over 10 years ago, the first successful gene therapy paradigms for experimental brain tumors models have been conducted, and they were thought to revolutionize the treatment of patients with gliomas. Application of gene therapy has been quickly forced into clinical trials, the first patients being enrolled in 1994, with overall results being disappointing. However, single patients seemed to benefit from gene therapy showing long-term treatment response, and most of these patients bearing small glioblastomas. Whereas the gene therapy itself has been performed with high sophistication, limited attention has been paid on technologies, which (i) allow an identification of viable target tissue in heterogenous glioma tissue and which (ii) enable an assessment of successful vector administration and vector-mediated gene expression in vivo. However, these measures are a prerequisite for the development of successful gene therapy in the clinical application. As biological treatment strategies such as gene and cell-based therapies hold promise to selectively correct disease pathogenesis, successful clinical implementation of these treatment strategies rely on the establishment of molecular imaging technology allowing the non-invasive assessment of endogenous and exogenous gene expression in vivo. Imaging endogenous gene expression will allow the characterization and identification of target tissue for gene therapy. Imaging exogenously introduced cells and genes will allow the determination of the 'tissue dose' of transduced cell function and vector-mediated gene expression, which in turn can be correlated to the induced therapeutic effect. Only these combined strategies of non-invasive imaging of gene expression in vivo will enable the establishment of safe and efficient vector administration and gene therapy protocols for clinical application. Here, we review some aspects of imaging in gene therapy trials for glioblastoma, and we present a 'proof-of-principle' 2nd-generation gene therapy protocol integrating molecular imaging technology for the establishment of efficient gene therapy in clinical application.
Motivation In an effort to provide a response to the ever-expanding generation of genomic data, the International Organization for Standardization (ISO) is designing a new solution for the representation, compression and management of genomic sequencing data: the Moving Picture Experts Group (MPEG)-G standard. This paper discusses the first implementation of an MPEG-G compliant entropy codec: GABAC. GABAC combines proven coding technologies, such as context-adaptive binary arithmetic coding, binarization schemes and transformations, into a straightforward solution for the compression of sequencing data. Results We demonstrate that GABAC outperforms well-established (entropy) codecs in a significant set of cases and thus can serve as an extension for existing genomic compression solutions, such as CRAM. Availability and implementation The GABAC library is written in C++. We also provide a command line application which exercises all features provided by the library. GABAC can be downloaded from https://github.com/mitogen/gabac. Supplementary information Supplementary data are available at Bioinformatics online.
The development and progress of high-throughput sequencing technologies have transformed the sequencing of DNA from a scientific research challenge to practice. With the release of the latest generation of sequencing machines, the cost of sequencing a whole human genome has dropped to less than $600. Such achievements open the door to personalized medicine, where it is expected that genomic information of patients will be analyzed as a standard practice. However, the associated costs, related to storing, transmitting, and processing the large volumes of data, are already comparable to the costs of sequencing. To support the design of new and interoperable solutions for the representation, compression, and management of genomic sequencing data, the Moving Picture Experts Group (MPEG) jointly with working group 5 of ISO/TC276 "Biotechnology" has started to produce the ISO/IEC
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