Sequence Analysis Tools
Sequence Analysis Tools - Related Videos
08:38
Targeted DNA Methylation Analysis by Next-generation Sequencing
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Cited by 83 •
2015
Bisulfite amplicon sequencing (BSAS) is a method for quantifying cytosine methylation in targeted genomic regions of interest. This method uses bisulfite conversion paired with PCR amplification of target regions prior to next-generation sequencing to produce absolute quantitation of DNA methylation at a base-specific level.
09:42
Using SecM Arrest Sequence as a Tool to Isolate Ribosome Bound Polypeptides
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Cited by 6 •
2012
We describe here a technique that is now routinely used to isolate stably bound ribosome nascent chain complexes (RNCs). This technique takes advantage of the discovery that a 17 amino acid long SecM "arrest sequence" can halt translation elongation in a prokaryotic (E. coli) system, when inserted into (or fused to the C-terminus) of virtually any protein.
08:16
Comparative Lesions Analysis Through a Targeted Sequencing Approach
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2019
This article describes a method to identify clonal and subclonal alterations among different specimens from a given patient. Although the experiments described here focus on a specific tumor type, the approach is broadly applicable to other solid tumors.
07:33
Nanopore DNA Sequencing for Metagenomic Soil Analysis
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Cited by 8 •
2017
Nanopore technology for sequencing biomolecules has wide applications in the life sciences, including identification of pathogens, food safety monitoring, genomic analysis, metagenomic environmental monitoring, and characterization of bacterial antibiotic resistance. In this article, the procedure for metagenomic soil DNA sequencing for species identification using the nanopore sequencing technology is demonstrated.
07:30
Optimization for Sequencing and Analysis of Degraded FFPE-RNA Samples
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Cited by 19 •
2020
This method describes the steps to improve the quality and quantity of sequence data that can be obtained from formalin-fixed paraffin-embedded (FFPE) RNA samples. We describe the methodology to more accurately assess the quality of FFPE-RNA samples, prepare sequencing libraries, and analyze the data from FFPE-RNA samples.
FAQs
Sequence alignment places reads or complete DNA, RNA, or protein sequences against a reference so corresponding positions can be compared. This makes mismatches visible and provides the basis for detecting sequence variants. In medical analysis, alignment converts raw sequence information into an organized comparison that can support diagnosis, disease investigation, and assessment of clinically relevant changes.
A reference genome supplies the standard sequence against which individual or pathogen-derived data can be examined. Differences from that reference can reveal mismatches and variants that may be biologically or clinically relevant. Without this comparison framework, sequence data would be more difficult to organize and interpret consistently across diagnostic or research investigations.
Variant detection identifies sequence differences, but databases and predictive algorithms help assess what those differences may signify. These resources provide interpretive context for connecting sequence patterns with potential biological or clinical effects. Their role is especially important when researchers need to move from identifying a change to evaluating its relevance for disease mechanisms or clinical decisions.
The analysis approach can begin with either individual sequencing reads or complete sequences. Reads are aligned to a reference to locate their corresponding positions, while complete sequences can be compared more broadly for similarities and differences. This flexibility allows sequence analysis tools to examine varied datasets while still supporting mismatch detection and biological interpretation.
A typical workflow processes sequence data, aligns reads or complete sequences with a reference, detects mismatches and variants, and then interprets findings using databases or predictive algorithms. The resulting information can be connected to clinical questions such as diagnosis, pathogen identification, cancer profiling, or treatment monitoring. Each stage progressively converts sequencing data into usable medical evidence.
For pathogen investigations, sequence analysis can compare DNA or RNA sequence data with reference genomes and identify patterns or similarities that support organism recognition. Detected sequence differences may also help characterize the analyzed pathogen. This application gives medicine a way to convert sequencing results into information relevant to identifying infectious agents and examining treatment-related mutations.
In genetic disease diagnosis, detected variants can be interpreted for their potential clinical relevance, helping clarify disease mechanisms. Similar analyses support cancer profiling and pharmacogenomics by examining sequence information in relation to disease or treatment. By organizing these findings, sequence analysis tools help guide clinical decisions and advance precision medicine.