Overview of Laboratory Management Resources

Updated: October 30, 2018

Edit this Page via GitHub       Comment by Filing an Issue      Have Questions? Ask them here.

A large part of any data generation process involves the effective organization and management of specimens and lab resources. Efficient lab management can streamline specimen receipt, processing, and any downstream data generation workflows. This section will highlight a few useful tools for the management of physical lab resources–tools for ordering and organizing reagents, helpful equipment for common lab workflows and a variety of guidance about assay material preparation, with specific tips for RNA and DNA based analysis approaches.

Assay Material Prep and QC

A critical component of quality large scale molecular data is quality assay material, in this case, the nucleic acid itself. Multiple processes are involved in the isolation and preparation of specimens and nucleic acids upstream of data generation that can impact both what types of data are feasible to generate, as well as what types of hypotheses the data can be used to address. Different data-generating platforms are sensitive to certain types of specimen quality and quantity. While the hypothesis for a study will narrow the choices for data types required, the quality and quantity of nucleic acids from a cohort of specimens can have an even larger impact on what data types are feasible, as well as the relevance and interpretability of the resulting data sets to the intended question. This page contains a summary of the types of nucleic acid isolation for different specimen types, the types of quality and quantity assessments and how these impact what downstream data generation process is applicable to the specimens of interest.

DNA-Based Approaches

Here we summarize some specific approaches to specimen processing, nucleic acid quality and quantity assessments, genomics platforms types, reagents, costs and data analysis requirements for DNA based data types such as hybridization or sequencing based techniques. We outline a few types of projects and give examples of the particular scientific considerations involved as well as some general guidelines about the costs of different approaches. We focus on non-whole genome studies but intend to provide some guidance from Fred Hutch researchers about this type of project in the future.

RNA-Based Approaches

Here we summarize some specific approaches to specimen processing, nucleic acid quality and quantity assessments, genomics platforms types, reagents, costs and data analysis requirements for RNA based data types such as hybridization or sequencing based techniques. We outline a few types of projects and give examples of the particular scientific considerations involved as well as some general guidelines about the costs of different approaches.

Support software

The organization of lab resource data is certainly not large scale data, but it can streamline lab workflows on a daily basis. For example, having a searchable database of PCR primers and their locations in freezers and boxes can save time in the planning and execution of assays. Alternatively, having an easily accessible communication platform among lab groups can facilitate transfer of knowledge about projects to new or existing lab members. This section will list some useful software platforms for organizing lab resources and communication.

Updated: October 30, 2018

Edit this Page via GitHub       Comment by Filing an Issue      Have Questions? Ask them here.