Multiplexed Sequencing
Multiplexed Sequencing - Related Videos
08:30
Multiplexed Single Cell mRNA Sequencing Analysis of Mouse Embryonic Cells
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Cited by 4 •
2020
Here we presented a multiplexed single cell mRNA sequencing method to profile gene expression in mouse embryonic tissues. The droplet-based single cell mRNA sequencing (scRNA-Seq) method in combination with multiplexing strategies can profile single cells from multiple samples simultaneously, which significantly reduces reagent costs and minimizes experimental batch effects.
10:15
Multiplex PCR and Reverse Line Blot Hybridization Assay (mPCR/RLB)
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Cited by 21 •
2011
An inexpensive, high throughput method for simultaneous detection of up to 43 molecular targets is described. Applications of mPCR/RLB include microbial typing and detection of multiple pathogens from clinical samples.
08:27
Use of a Caspase Multiplexing Assay to Determine Apoptosis in a Hypothalamic Cell Model
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Cited by 20 •
2014
Multiplex assays can provide beneficial information for basic cellular mechanisms and eliminate waste of reagents and unnecessary repetitive experiments. We describe here a multiplex caspase-3/7 activity assay, using fluorescent- and luminescent-based methods, to determine cell viability in an in vitro hypothalamic model following oxidative challenge with palmitic acid.
09:49
Oncogenic Gene Fusion Detection Using Anchored Multiplex Polymerase Chain Reaction Followed by Next Generation Sequencing
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Cited by 13 •
2019
This article details the use of an anchored multiplex polymerase chain reaction-based library preparation kit followed by next-generation sequencing to assess for oncogenic gene fusions in clinical solid tumor samples. Both wet-bench and data analysis steps are described.
08:57
Amplicon Sequencing using the Long-Read Sequencing Technologies
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2025
This protocol was optimized for targeted deep sequencing of 18 drug-resistance regions in Mycobacterium tuberculosis using a long-read sequencing platform, followed by analysis with a tuberculosis-specific bioinformatics pipeline designed for long-read data.
FAQs
Unique molecular barcodes, also called indexes, identify the sample associated with each sequenced read. During library preparation, a different barcode is attached to each sample, allowing computational demultiplexing to sort reads back to their sources after the run. Accurate assignment is essential because subsequent alignment and variant analysis depend on separating the combined sequencing output correctly.
Demultiplexing separates reads according to their original samples before those reads are interpreted. If reads remained combined, alignment and variant analysis could mix molecular information from different patients, targets, or genomic regions. Performing the steps in sequence preserves sample-specific results and allows downstream analyses to connect detected sequence changes with the appropriate biological source.
Analyzing multiple samples or targets in one sequencing run makes better use of available sequencing capacity. It can also reduce the cost assigned to each sample and conserve biological material, because laboratories obtain information from several inputs without requiring a separate run for every one. This scalability is especially useful when broader molecular testing is needed.
The workflow begins with library preparation, during which unique barcodes or indexes are attached to individual samples. Multiple prepared inputs then undergo sequencing in the same run. Computational demultiplexing assigns resulting reads to their sources, after which the separated data can undergo alignment and variant analysis. This sequence preserves the link between each read and its originating sample.
In medicine, multiplexed sequencing supports inherited disease diagnosis, cancer profiling, infectious disease surveillance, and treatment selection. Laboratories can examine multiple patient samples, genes, or genomic regions within a coordinated analysis. The resulting broader molecular information can help characterize disease-related sequence variation and support decisions that depend on patient-specific or pathogen-related genomic findings.
Treatment selection can draw on molecular information obtained from several genes or genomic regions analyzed together. By expanding the amount of sequence data generated from a patient’s material, the approach can support evaluation of variation relevant to clinical decision-making. Its value lies in combining scalable testing with downstream alignment and variant analysis rather than relying on a single molecular target.