differential expression - What does an FDR value of 1 in RNA-seq …
2018年12月3日 · FDR stands for False Discovery Rate.It is a statistic tool used in multiple hypothesis testing. As you may know, when you use a p-value cutoff (usually 0.05) for your experiments, it means strictly speaking that "is there was actually no signal, there would be a probability of 0.05 to obser
rna seq - Are mitochondrial genes to exclude in scRNA-seq such …
You might catch a few lucky ribosomal RNA (Rn45s) copies that were transcribed recently and still haven't been processed, but depending on your RNA-seq protocol, there's a chance they are acting as a functional part of the ribosome rather than an intermediate stage. $\endgroup$ –
rna seq - How can we distinguish between true zero and dropout …
2017年6月13日 · In single-cell RNA-seq data we have an inflated number of 0 (or near-zero) counts due to low mRNA capture rate and other inefficiencies. How can we decide which genes are 0 due to gene dropout (lack of measurement sensitivity), and which are genuinely not expressed in the cell?
5' and 3' bias in Rna-seq data - Bioinformatics Stack Exchange
2018年2月19日 · I'm working with rna-seq samples. I see 5' bias and also 3' bias in the per-base sequence content plot. From this link I see that the bias at the start of the sequences appears to be the result of biased selection of fragments from the library. And this won't effect any downstream analysis.
rna seq - Which measure should be used in a PCA or RNA-seq …
2017年8月18日 · I'm trying to understand the magnitude of batch effects in my RNA-seq samples, and I was wondering which expression units are more suitable to draw a PCA. I'm thinking of either counts or TPM, but things like rlog or vst could work too.
rna seq - Negative binomial modeling of RNA-Seq data
A common way to model RNA-seq data is using a negative binomial distribution, where each sample-gene pair ...
Show presence of known mutation in RNA-seq data
We have RNA-seq fastq data from control (WT) patients and a patient with a point mutation at a known location in one gene. I'd like to retrieve the reads aligning to that gene and show the presence of the mutation. I can think of 2 strategies: A) Alignment and visualization, based on GATK: Run STAR 2-pass. Extract alignments of interest, e.g.:
Why total RNA-seq usually yields low mapping rate?
2017年11月22日 · A likely explanation is that total RNA-Seq contains a high fraction of reads from ribosomal RNAs. Ribosomal RNAs are present in multiple copies across the genome, hence many reads map to multiple genomic locations and get discarded by the aligner.
rna seq - The confusion of using TPM (transcripts per million ...
2021年7月14日 · When I analyzed sc-RNA seq data, the Seurat package uses normalized counts (which is CPM) for DEG, but TPM is not advised for differential testing. I'm not sure what I'm missing in the understanding. It seems very convoluted to me.
rna seq - How exactly is "effective length" used in FPKM calculated ...
I have a blog post that describes the effective length (as well as these different relative abundance units). ). The short explanation is that what people refer to as the "effective length" is actually the expected effective length (i.e., the expectation, in a statistical sense, of the effective le