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RNA-seq

RNA-seq

RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases.
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while...

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Novel Sequence Discovery by Subtractive Genomics

Novel Sequence Discovery by Subtractive Genomics

Published on: January 25, 2019

Compact variant-rich customized sequence database and a fast and sensitive database search for efficient

Heejin Park¹, Junwoo Bae, Hyunwoo Kim

¹Department of Computer Science and Engineering, Hanyang University, Seoul, Republic of Korea.

|October 16, 2014

Summary

This summary is machine-generated.

This study introduces a novel method for proteogenomic analysis, creating compact variant peptide databases from sequencing data. This approach enhances protein identification sensitivity and speed, improving variant detection in complex proteomes.

Keywords:

Bioinformatics Early onset gastric cancer Peptide identification Proteogenomics Sequence database

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An Integrated Approach for Microprotein Identification and Sequence Analysis

An Integrated Approach for Microprotein Identification and Sequence Analysis

Published on: July 12, 2022

Area of Science:

Proteomics
Genomics
Bioinformatics

Background:

Accurate proteogenomic analysis relies on customized databases and sensitive search strategies for variant detection.
Current methods for database construction and searching are often ad-hoc, lacking systematic optimization.
Identifying protein-level variations requires efficient integration of genomic and transcriptomic data.

Purpose of the Study:

To develop an effective method for constructing compact, customized proteogenomic databases.
To present an efficient search strategy that balances speed and sensitivity for variant peptide identification.
To facilitate the inspection of peptide-spectrum matches by including mutation information.

Main Methods:

Constructed a compact database storing variant peptides (SNVs, indels, stop-codon mutations) derived from Exome-seq and RNA-seq data.
Developed a unified search method that performs target-decoy validations separately for enhanced sensitivity.
Integrated mutation information into variant peptide headers for easier analysis.

Main Results:

The customized database effectively stores variant information with reduced space requirements.
The proposed search method achieves speed comparable to unified searches and sensitivity similar to separate searches.
Mutation information in peptide headers aids in the interpretation of peptide-spectrum matches.

Conclusions:

The developed method provides an efficient and sensitive approach for proteogenomic database construction and searching.
This systematic approach improves the accuracy of protein abundance and structural variation determination.
Facilitates deeper insights into proteomic variations and their functional implications.