This article explores the opportunities and challenges in designing and implementing a monitoring and evaluation (M&E) framework for a consortium-run, multi-country international development program. The East Asia Vision Program (EAVP), a three-year program of the Vision 2020 Australia Global Consortium, aims to improve capacity in the delivery of eye health and vision care services in Vietnam, Cambodia, and Timor-Leste. Funded by the Australian Government, the EAVP began in 2013 and consists of five Australian organisations working with government and other stakeholders in each country. The Consortium members have been working in collaboration to support national government planning, health professional training, patient treatment, and research capacity through monitoring and evaluation. An M&E Reference Group helped with initial drafts of an M&E framework. Australian and in-country staff were then consulted to ensure availability of data and understanding of the Framework. Early drafts of data entered into the framework were shared between the participating organisations and the evaluator in order to detect errors and share good practice examples using online program management software. Monitoring the program provided an opportunity for Consortium members to improve program implementation and strengthen their capacity for M&E, by sharing examples of evaluation tools and expertise in the monitoring of cross-cutting issues and data collection. The combined work of the organisations within each country provided a rich dataset of outcomes at a health systems strengthening level. Challenges faced during the evaluation included: aligning the evaluation systems of all organisations (including data that were feasible to collect); monitoring a large range of activities; and developing an evaluation tool that was usable by a diverse range of staff. This article reports the perspectives of the M&E Advisor for EAVP and those of a program implementer to share learnings regarding the M&E for a consortium-run program. Consortia are used globally to implement international development programs and they present a unique challenge for evaluators. These consortia also provide the opportunity to build the monitoring and evaluation capacity of participating organisations, leading to improved data quality and better-informed program implementation.
High throughput sequencing technologies are currently revolutionizing the cancer research area with rapid improvements in sequencing capacity and time consumption. As a result the most time consuming step has moved from being the sequencing process itself to being the bioinformatic data analysis. RNA sequencing (RNA-Seq) is used in an increasing number of transcriptomic studies. The great advantage of using RNA-Seq is its ability to precisely quantify transcript levels and identify novel transcripts, isoforms, and splice junctions, while further providing information of the mutational landscape down to single base resolution. To ease the hurdles associated with RNA-Seq data analysis there is an increasing demand for tools that are specifically tailored to RNA-Seq data. Here we describe how the newly developed CLC Cancer Research Workbench can be used to analyze and visualize RNA-Seq data with ready-to-use workflows that automatically map, quantify, and annotate transcriptomes. We identify differentially expressed genes and transcripts in Illumina HiSeq transcriptomic data from matched tumor and normal samples from four esophageal adenocarinoma cancer patients, and compare the mutational patterns in the samples with the expression values of the corresponding genes. Results are visualized in a track based genome browser view, which provides the means for quick and easy navigation as well as allowing the user to simultaneously view and annotate multiple samples and different data types (e.g. genes, transcript expression levels, and detected variants). Citation Format: Bodil Oster, Anika Joecker, Anne-Mette K. Hein, Patrick Dekker, Robert O'Neill, Adam Krejci, Anne Arens, Naomi Thomson, Cecilie Boysen, Søren Mønsted, Roald Forsberg, Bjarne Knudsen, Thomas Knudsen, Richard Lussier, Ted R. Hupp. Identification of differentially expressed genes and somatic mutations in esophageal adenocarinoma cancer patients. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 2334. doi:10.1158/1538-7445.AM2014-2334
The now commonplace application of whole exome and genome sequencing in cancer research and diagnostics has allowed for rapid identification of SNPs and InDels in protein coding regions, but neither method is able to reveal situations of incomplete penetrance. That is, while possible cancer causing allele variants can be detected with these methods, this does not mean these alleles are actually expressed. Reasons for this are various and include epigenetic effects and changes, transcription regulation mechanisms, mRNA degradation and epistasis. By contrast, transcriptome sequencing (RNA-seq) can be used to identify the alleles being expressed. This method has the additional benefits of providing insight into the transcript expression levels, expressed allele isoforms and offers the possibility of identifying instances of fusion transcripts. Such knowledge about variants expressed in tumor cells is crucial for the identification of effective drug targets. Here, we illustrate the benefits of combining whole exome sequencing with RNA-seq by analyzing whole exome and RNA-seq datasets from uveal melanoma samples with our newly developed CLC Cancer Research Workbench. This software suite enables the complete analysis of both approaches, including variant calling, followed by the comparison of the called variants. The analysis will be carried out using user-friendly, automated workflows distributed with the CLC Cancer Research Workbench. In this work, we discuss and compare variants identified in the exome and RNA-seq datasets using our algorithms, and focus particularly on variants identified in the exome data that appear not to be expressed in the tumor samples. Citation Format: Anne Arens, Anne-Mette K. Hein, Uwe Appelt, Anika Joecker, Søren Mønsted, Bjarne Knudsen, Naomi Thomson, Richard Lussier, Cecilie Boysen, Roald Forsberg. Comparison of variant calling from whole exome and transcriptome sequencing using CLC Cancer Research Workbench. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 5332. doi:10.1158/1538-7445.AM2014-5332
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.