TECHNIQUES FOR DIAGNOSING SOURCES OF ERROR IN A SAMPLE PROCESSING WORKFLOW
Techniques for identifying sources of error occurring during processing of biological samples in a laboratory environment. The techniques may include obtaining data about the biological samples, where the data is generated by processing the biological samples in accordance with a sample processing workflow. The sample processing workflow is performed using physical component(s) and/or workflow process(es). The techniques further include determining values of quality metric(s) associated with the sample processing workflow for the biological samples, identifying source(s) of error for the data by using the values of the quality metric(s) and statistical model representing causal relationships among the physical component(s) and the workflow process(es), and outputting information indicative of the identified source(s) of error.
1 . A method for identifying sources of error occurring during processing of biological samples in a laboratory environment in accordance with a sample processing workflow, the sample processing workflow being performed using one or more physical components and/or one or more workflow processes, the sample processing workflow being associated with at least one quality metric, the method comprising:
using at least one computer hardware processor to perform:
obtaining data about a plurality of biological samples, the data generated by processing the plurality of biological samples in accordance with the sample processing workflow;
determining, using the data, values of the at least one quality metric for each of at least some of the plurality of biological samples;
identifying one or more sources of error for the data generated by processing the plurality of biological samples, the identifying performed using the values of the at least one quality metric and a statistical model representing causal relationships among the one or more physical components and/or the one or more workflow processes used to perform the sample processing workflow; and
outputting information indicative of the identified one or more sources of error.
2 . The method of claim 1 , wherein the information indicative of the identified one or more sources of error indicates a physical component, from among the one or more physical components used to perform the sample processing workflow, as a source of error for the data generated by processing the plurality of biological samples in accordance with the sample processing workflow.
3 . The method of claim 2 , wherein the physical component is a piece of equipment used to perform at least one workflow process of the sample processing workflow, and outputting information further comprises outputting information identifying the piece of equipment.
4 . The method of claim 2 , wherein the physical component is a reagent from a lot used to perform at least one workflow process of the sample processing workflow, and outputting information further comprises outputting information identifying the lot as a source of error for the data generated by processing the plurality of biological samples in accordance with the sample processing workflow.
5 . The method of claim 1 , wherein the information indicative of the identified one or more sources of error indicates a workflow process, from among the one or more workflow processes used to perform the sample processing workflow, as a source of error for the data generated by processing the plurality of biological samples in accordance with the sample processing workflow.
6 . The method of claim 1 , wherein the information indicative of the identified one or more sources of error indicates one or more of the plurality of biological samples as a source of error for the data generated by processing the plurality of biological samples in accordance with the sample processing workflow.
7 . The method of claim 1 , further comprising processing the plurality of biological samples in accordance with the sample processing workflow.
8 . The method of claim 1 , wherein the one or more physical components include one or more reagents used in the sample processing workflow and/or one or more pieces of equipment used in the sample processing workflow.
9 . The method of claim 8 , wherein the one or more physical components include at least one physical component selected from the group consisting of: an extraction machine, an extraction automation system, a library preparation automation system, a thermocycler, an automation system, a sequencing machine, a hybridization machine, a centrifugation machine, a liquid handling system, and a qPCR machine.
10 . The method of claim 8 , wherein the one or more physical components include at least one reagent selected from the group consisting of: a buffer, a binding buffer, a wash buffer, an organic reagent, an inorganic reagent, an acidic solution, and a basic solution.
11 . The method of claim 8 , wherein the one or more physical components include at least one selected from the group consisting of: a bait mix, a hybridization mix, a sequencing mix, a PCR master mix, and a primer mix.
12 . The method of claim 8 , wherein the one or more physical components include at least one selected from the group consisting of: an enzyme, a labeled nucleotide, a sample plate, enrichment beads, a flow cell, a cartridge, a pipette, a pipette tip, and a sample tube.
13 . The method of claim 8 , wherein the one or more workflow processes include at least one workflow process selected from the group consisting of: an extraction process, a library preparation process, an enrichment process, a hybridization process, a sequencing process, a centrifugation process, an assay setup process, an amplification process, and a qPCR process.
14 . The method of claim 8 , wherein the one or more workflow processes include a sequencing process, the one or more physical components include at least one sequencing machine and at least one sequencing reagent, the data includes sequencing data for each of the at least some of the plurality of biological samples, and the at least one quality metric includes sequencing metrics for the sequencing data.
15 . The method of claim 14 , wherein the statistical model represents causal relationships among the at least one sequencing machine, the at least one sequencing reagent, the plurality of biological samples, and the sequencing data.
16 - 21 . (canceled)
22 . The method of claim 1 , wherein the statistical model comprises a graphical model comprising:
nodes representing random variables corresponding to at least some of the one or more physical components and/or at least some of the one or more workflow processes; and
directed edges representing causal relationships among the at least some of the one or more physical components and/or the at least some of the one or more workflow processes.
23 - 27 . (canceled)
27 . The method of claim 22 , wherein a node corresponding to a physical component of the sample processing workflow represents a random variable whose value is indicative of a degree to which the physical component contributes to error in the data generated by processing biological samples in accordance with the sample processing workflow.
28 . The method of claim 22 , wherein a node corresponding to a workflow process of the sample processing workflow represents a random variable whose value is indicative of a degree to which the workflow process contributes to error in the data generated by processing biological samples in accordance with the sample processing workflow.
29 - 31 . (canceled)
32 . A system for identifying sources of error occurring during processing of biological samples in a laboratory environment in accordance with a sample processing workflow, the sample processing workflow being performed using one or more physical components and/or one or more workflow processes, the sample processing workflow being associated with at least one quality metric, the system comprising:
at least one hardware processor; and
at least one non-transitory computer-readable storage medium storing processor-executable instructions that, when executed by the at least one hardware processor, cause the at least one hardware processor to perform:
obtaining data about a plurality of biological samples, the data generated by processing the plurality of biological samples in accordance with the sample processing workflow;
determining, using the data, values of the at least one quality metric for each of at least some of the plurality of biological samples;
identifying one or more sources of error for the data generated by processing the plurality of biological samples, the identifying performed using the values of the at least one quality metric and a statistical model representing causal relationships among the one or more physical components and/or the one or more workflow processes used to perform the sample processing workflow; and
outputting information indicative of the identified one or more sources of error.
33 . At least one non-transitory computer-readable storage medium storing processor-executable instructions that, when executed by at least one hardware processor, cause the at least one hardware processor to perform a method for identifying sources of error occurring during processing of biological samples in a laboratory environment in accordance with a sample processing workflow, the sample processing workflow being performed using one or more physical components and/or one or more workflow processes, the sample processing workflow being associated with at least one quality metric, the method comprising:
using at least one computer hardware processor to perform:
obtaining data about a plurality of biological samples, the data generated by processing the plurality of biological samples in accordance with the sample processing workflow;
determining, using the data, values of the at least one quality metric for each of at least some of the plurality of biological samples;
identifying one or more sources of error for the data generated by processing the plurality of biological samples, the identifying performed using the values of the at least one quality metric and a statistical model representing causal relationships among the one or more physical components and/or the one or more workflow processes used to perform the sample processing workflow; and
outputting information indicative of the identified one or more sources of error.
34 .- 55 . (canceled)