Is it time for standards and a common data exchange format for digital image analysis?

Digital image analysis is at a crossroads. While the technology has made great strides over the past few decades, there is an urgent need for image analysis to inform the next wave of large scale tissue biomarker discovery studies in cancer. Drawing parallels from the growth of next generation sequencing, this presentation will consider the case for a common language or standard format for storing and communicating digital image analysis data. In this context, image analysis data comprises more than simply an image with markups and attached key-value pair metrics. The desire to objectively benchmark competing platforms or a push for data to be deposited to public repositories much like genomics data may drive the need for a standard that also encompasses granular, cell-by-cell data.

The Interlaboratory Robustness Of Next-Generation Sequencing (IRON) Study Phase II: Deep-Sequencing Analyses Of Hematological Malignancies Performed In 8,867 Cases By An International Network Involving 27 Laboratories

Introduction: Amplicon deep-sequencing using second-generation sequencing technology is an innovative molecular diagnostic technique and enables a highly-sensitive detection of mutations. As an international consortium we had investigated previously the robustness, precision, and reproducibility of 454 amplicon next-generation sequencing (NGS) across 10 laboratories from 8 countries (Leukemia, 2011;25:1840-8).

Aims: In Phase II of the study, we established distinct working groups for various hematological malignancies, i.e. acute myeloid leukemia (AML), acute lymphoblastic leukemia (ALL), chronic lymphocytic leukemia (CLL), chronic myelogenous leukemia (CML), myelodysplastic syndromes (MDS), myeloproliferative neoplasms (MPN), and multiple myeloma. Currently, 27 laboratories from 13 countries are part of this research consortium. In total, 74 gene targets were selected by the working groups and amplicons were developed for a NGS deep-sequencing assay (454 Life Sciences, Branford, CT). A data analysis pipeline was developed to standardize mutation interpretation both for accessing raw data (Roche Amplicon Variant Analyzer, 454 Life Sciences) and variant interpretation (Sequence Pilot, JSI Medical Systems, Kippenheim, Germany).

Results: We will report on the design, standardization, quality control aspects, landscape of mutations, as well as the prognostic and predictive utility of this assay in a cohort of 8,867 cases. Overall, 1,146 primer sequences were designed and tested. In detail, for example in AML, 924 cases had been screened for CEBPA mutations. RUNX1 mutations were analyzed in 1,888 cases applying the deep-sequencing read counts to study the stability of such mutations at relapse and their utility as a biomarker to detect residual disease. Analyses of DNMT3A (n=1,041) were focused to perform landscape investigations and to address the prognostic relevance. Additionally, this working group is focusing on TET2, ASXL1, and TP53 analyses. A novel prognostic model is being developed allowing stratification of AML into prognostic subgroups based on molecular markers only. In ALL, 1,124 pediatric and adult cases have been screened, including 763 assays for TP53 mutations both at diagnosis and relapse of ALL. Pediatric and adult leukemia expert labs developed additional content to study the mutation incidence of other B and T lineage markers such as IKZF1, JAK2, IL7R, PAX5, EP300, LEF1, CRLF2, PHF6, WT1, JAK1, PTEN, AKT1, IL7R, NOTCH1, CREBBP, or FBXW7. Further, the molecular landscape of CLL is changing rapidly. As such, a separate working group focused on analyses including NOTCH1, SF3B1, MYD88, XPO1, FBXW7 and BIRC3. Currently, 922 cases were screened to investigate the range of mutational burden of NOTCH1 mutations for their prognostic relevance. In MDS, RUNX1 mutation analyses were performed in 977 cases. The prognostic relevance of TP53 mutations in MDS was assessed in additional 327 cases, including isolated deletions of chromosome 5q. Next, content was developed targeting genes of the cellular splicing component, e.g. SF3B1, SRSF2, U2AF1, and ZRSR2. In BCR-ABL1-negative MPN, nine genes of interest (JAK2, MPL, TET2, CBL, KRAS, EZH2, IDH1, IDH2, ASXL1) have been analyzed in a cohort of 155 primary myelofibrosis cases searching for novel somatic mutations and addressing their relevance for disease progression and leukemia transformation. Moreover, an assay was developed and applied to CMML cases allowing the simultaneous analysis of 25 leukemia-associated target genes in a single sequencing run using just 20 ng of starting DNA. Finally, nine laboratories are studying CML, applying ultra-deep sequencing of the BCR-ABL1 tyrosine kinase domain. Analyses were performed on 615 cases investigating the dynamics of expansion of mutated clones under various tyrosine kinase inhibitor therapies.

Conclusion: Molecular characterization of hematological malignancies today requires high diagnostic sensitivity and specificity. As part of the IRON-II study, a network of laboratories analyzed a variety of disease entities applying amplicon-based NGS assays. Importantly, the consortium not only standardized assay design for disease-specific panels, but also achieved consensus on a common data analysis pipeline for mutation interpretation. Distinct working groups have been forged to address scientific tasks and in total 8,867 cases had been analyzed thus far.

A review of ADP processing software

Data processing is an essential part of Acoustic Doppler Profiler (ADP) surveys, which have become the standard tool in assessing flow characteristics at tidal power development sites. In most cases, further processing beyond the capabilities of the manufacturer provided software tools is required. These additional tasks are often implemented by every user in mathematical toolboxes like MATLAB, Octave or Python. This requires the transfer of the data from one system to another and thus increases the possibility of errors. The application of dedicated tools for visualisation of flow or geographic data is also often beneficial and a wide range of tools are freely available, though again problems arise from the necessity of transferring the data. Furthermore, almost exclusively PCs are supported directly by the ADP manufacturers, whereas small computing solutions like tablet computers, often running Android or Linux operating systems, seem better suited for online monitoring or data acquisition in field conditions. While many manufacturers offer support for developers, any solution is limited to a single device of a single manufacturer. A common data format for all ADP data would allow development of applications and quicker distribution of new post processing methodologies across the industry.

Methodological variations in estimating apparent progressive visual field loss in clinical trials of glaucoma treatment.

OBJECTIVES:

To compare methods to estimate the incidence of visual field progression used by 3 large randomized trials of glaucoma treatment by applying these methods to a common data set of annually obtained visual field measurements of patients with glaucoma followed up for an average of 6 years.

METHODS:

The methods used by the Advanced Glaucoma Intervention Study (AGIS), the Collaborative Initial Glaucoma Treatment Study (CIGTS), and the Early Manifest Glaucoma Treatment study (EMGT) were applied to 67 eyes of 56 patients with glaucoma enrolled in a 10-year natural history study of glaucoma using Program 30-2 of the Humphrey Field Analyzer (Humphrey Instruments, San Leandro, Calif). The incidence of apparent visual field progression was estimated for each method. Extent of agreement between the methods was calculated, and time to apparent progression was compared.

RESULTS:

The proportion of patients progressing was 11%, 22%, and 23% with AGIS, CIGTS, and EMGT methods, respectively. Clinical assessment identified 23% of patients who progressed, but only half of these were also identified by CIGTS or EMGT methods. The CIGTS and the EMGT had comparable incidence rates, but only half of those identified by 1 method were also identified by the other.

CONCLUSIONS:

The EMGT and CIGTS methods produced rates of apparent progression that were twice those of the AGIS method. Although EMGT, CIGTS, and clinical assessment rates were comparable, they did not identify the same patients as having had field progression.

Thermal environments and comfort in dementia friendly dwellings

This study follows on from a research project that developed guidelines for the Universal Design (UD) of Dementia Friendly Dwellings for People with Dementia, their Families and Carers. Research findings point to the need for thermal environments that support people with dementia and do not provoke stress, agitation or anxiety. Using semi-structured interviews and qualitative analysis of people with dementia this paper aims to provide insight into the questions of appropriate thermal environments. The qualitative analysis is supported by example simulated indoor environment studies that investigate comfort in common thermal environment provision scenarios in the homes of people with dementia. This paper focuses on the thermal environment, its impact on people with dementia, its therapeutic value, and its role in encouraging engagement in every day activity.
Findings from the interviews emphasize that control over their own internal environment is a priority for people with dementia. A strong preference for naturally or passively conditioned environments over mechanical conditioning is evident. Preferences are expressed for naturally ventilated environments enabling occupant instigated air movement. Repeated emphasis is placed on familiar elements including the fire and hot water bottle. Little desire is expressed for information feedback or technological displays.

Quantifying heritable variation in fitness-related traits of wild, farmed and hybrid Atlantic salmon families in a wild river environment

Farmed fish are typically genetically different from wild conspecifics. Escapees from fish farms may contribute one-way gene flow from farm to wild gene pools, which can depress population productivity, dilute local adaptations and disrupt coadapted gene complexes. Here, we reanalyse data from two experiments (McGinnity et al., 1997, 2003) where performance of Atlantic salmon (Salmo salar) progeny originating from experimental crosses between farm and wild parents (in three different cohorts) were measured in a natural stream under common garden conditions. Previous published analyses focussed on group-level differences but did not account for pedigree structure, as we do here using modern mixed-effect models. Offspring with one or two farm parents exhibited poorer survival in their first and second year of life compared with those with two wild parents and these group-level inferences were robust to excluding outlier families. Variation in performance among farm, hybrid and wild families was generally similar in magnitude. Farm offspring were generally larger at all life stages examined than wild offspring, but the differences were moderate (5–20%) and similar in magnitude in the wild versus hatchery environments. Quantitative genetic analyses conducted using a Bayesian framework revealed moderate heritability in juvenile fork length and mass and positive genetic correlations (>0.85) between these morphological traits. Our study confirms (using more rigorous statistical techniques) previous studies showing that offspring of wild fish invariably have higher fitness and contributes fresh insights into family-level variation in performance of farm, wild and hybrid Atlantic salmon families in the wild. It also adds to a small, but growing, number of studies that estimate key evolutionary parameters in wild salmonid populations. Such information is vital in modelling the impacts of introgression by escaped farm salmon.

Open Source Telecommunications Framework for Time-Series Data from Smart Grid Sensors.

This paper presents a framework for a telecommunications interface which allows data from sensors embedded in Smart Grid applications to reliably archive data in an appropriate time-series database. The challenge in doing so is two-fold, firstly the various formats in which sensor data is represented, secondly the problems of telecoms reliability. A prototype of the authors' framework is detailed which showcases the main features of the framework in a case study featuring Phasor Measurement Units (PMU) as the application. Useful analysis of PMU data is achieved whenever data from multiple locations can be compared on a common time axis. The prototype developed highlights its reliability, extensibility and adoptability; features which are largely deferred from industry standards for data representation to proprietary database solutions. The open source framework presented provides link reliability for any type of Smart Grid sensor and is interoperable with existing proprietary database systems, and open database systems. The features of the authors' framework allow for researchers and developers to focus on the core of their real-time or historical analysis applications, rather than having to spend time interfacing with complex protocols.

Compositional data analysis of Holocene sediments from the West Bengal Sundarbans, India: Geochemical proxies for grain-size variability in a delta environment

This paper is part of a special issue of Applied Geochemistry focusing on reliable applications of compositional multivariate statistical methods. This study outlines the application of compositional data analysis (CoDa) to calibration of geochemical data and multivariate statistical modelling of geochemistry and grain-size data from a set of Holocene sedimentary cores from the Ganges-Brahmaputra (G-B) delta. Over the last two decades, understanding near-continuous records of sedimentary sequences has required the use of core-scanning X-ray fluorescence (XRF) spectrometry, for both terrestrial and marine sedimentary sequences. Initial XRF data are generally unusable in ‘raw-format’, requiring data processing in order to remove instrument bias, as well as informed sequence interpretation. The applicability of these conventional calibration equations to core-scanning XRF data are further limited by the constraints posed by unknown measurement geometry and specimen homogeneity, as well as matrix effects. Log-ratio based calibration schemes have been developed and applied to clastic sedimentary sequences focusing mainly on energy dispersive-XRF (ED-XRF) core-scanning. This study has applied high resolution core-scanning XRF to Holocene sedimentary sequences from the tidal-dominated Indian Sundarbans, (Ganges-Brahmaputra delta plain). The Log-Ratio Calibration Equation (LRCE) was applied to a sub-set of core-scan and conventional ED-XRF data to quantify elemental composition. This provides a robust calibration scheme using reduced major axis regression of log-ratio transformed geochemical data. Through partial least squares (PLS) modelling of geochemical and grain-size data, it is possible to derive robust proxy information for the Sundarbans depositional environment. The application of these techniques to Holocene sedimentary data offers an improved methodological framework for unravelling Holocene sedimentation patterns.