How much is RNA seq per sample?
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| Papers (10) | Insight |
|---|---|
| By obtaining tens or even hundreds of millions of reads of transcribed sequences, an RNA-Seq experiment can offer a comprehensive survey of the population of genes (transcripts) in any sample of interest. | |
| The reduction in performance compared with bulk RNA-seq is small. | |
186 Citations | In addition, RNA-seq is of particular value when low RNA expression or modest changes between samples are monitored. |
| Consequently, it is a pivotal parameter to consider when designing an RNA-Seq experiment. | |
| Low quantities of starting RNA can be a severe hindrance for studies that aim to utilize RNA-Seq. | |
| However, such a bias has not been systematically analyzed for different replicate types of RNA-seq data. We show that the dispersion coefficient of a gene in the negative binomial modeling of read counts is the critical determinant of the read count bias (and gene length bias) by mathematical inference and tests for a number of simulated and real RNA-seq datasets. | |
| We evaluate the methods based on both simulated data and real RNA-seq data. Very small sample sizes, which are still common in RNA-seq experiments, impose problems for all evaluated methods and any results obtained under such conditions should be interpreted with caution. | |
| They indicated limited utility of sample pooling strategies for RNA-seq in similar setups and supported increasing the number of biological replicate samples. | |
31 Citations | This report presents a simple, rapid, and inexpensive method for preparing strand-specific RNA-Seq libraries from varying quantities of total RNA. |
| Because the field currently lacks a sample size calculation method based on the negative binomial model for assessing differential expression analysis of RNA-seq data, we propose a method to calculate the sample size. We propose a sample size calculation method based on the exact test for assessing differential expression analysis of RNA-seq data. The proposed sample size calculation method is straightforward and not computationally intensive. |
Related Questions
Amount of starting material for RNA extraction for RNA sequencing4 answersRNA sequencing (RNA-seq) can be performed using low amounts of starting material, ranging from 10 pg to 10 ng of total RNA or 1-1000 intact cells. For gene expression analysis from seed tissues, high-quality RNA can be extracted using only 2 to 3 mg of starting tissue. A new RNA-Seq library preparation technique has been developed that allows representative, strand-specific RNA-Seq libraries to be generated from small amounts of starting material in a fast and cost-effective manner. RNA can also be extracted from dried blood spots (DBS) for transcriptome studies, providing an option when field conditions make it difficult to collect, store, or transport whole blood for RNA studies. Additionally, a miniSAGE technique has been established for determining gene expression patterns using as little as 1 μg of RNA as starting material.
How to analyze RNA seq with tumor sample?3 answersRNA-seq analysis with tumor samples involves several steps. First, a systematic examination of single-cell RNA-seq clustering algorithms can be performed to reflect the heterogeneity of cell populations in cancer samples. This can help cluster single-cell profiles into groups that reflect the underlying cell types. Additionally, a highly customizable workflow for single-cell data analysis can be used, which includes steps such as quality control, preprocessing, clustering, and identification of gene markers. Another approach is to use RNA-seq data alone for somatic variant detection and driver mutation analysis. This can be done using a containerized pipeline called RNA-VACAY, which automates somatic variant calling from tumor RNA-seq data. Finally, for the quantification of tumor immune infiltrates, the computational pipeline quanTIseq can be used to analyze bulk RNA-seq data from tumor samples. These approaches provide valuable insights into the biology and characteristics of tumors and can aid in cancer research and treatment.
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