User: bigitharulesforever

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Posts by bigitharulesforever

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Comment: C: How can you use normalised count matrix for differential gene expression analysi
... Would it be okay to round up the quality-controlled counts to integer value for the DESeq2 / EdgeR programs? As essentially, it does not include any outlier probes or data that can skew the overall analysis but the data is not normalised either. Also, I am trying to use EnhancedVolcano package, is ...
written 9 days ago by bigitharulesforever0
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Comment: C: How can you use normalised count matrix for differential gene expression analysi
... Hi Kevin, Thank you so much for your help so far. I just wanted to clear something up. If I was to perform a normalisation for quality controlled counts, which average type would be the best: geometric mean, median, average, minimum, maximum or third quartile? ...
written 10 days ago by bigitharulesforever0
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Comment: C: How can you use normalised count matrix for differential gene expression analysi
... I did some digging into what the values are and according to a webinar on this particular experiment type done by nanostring the values are: "Multiple probes targeting the same transcript are molecularly barcoded and quantitated such that there are up to 10 independent counts per transcript which a ...
written 11 days ago by bigitharulesforever0
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Comment: C: How can you use normalised count matrix for differential gene expression analysi
... However, if I was to take the mean then I wouldn't be able to use DESeq2 or EdgeR right? As they both only take raw counts? ...
written 11 days ago by bigitharulesforever0
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Comment: C: How can you use normalised count matrix for differential gene expression analysi
... Thank you Kevin, I was able to obtain a bit more background information on my data. It is using Nanostring's RNA assay with next-generation sequencing readout. My raw counts look like this: ProbeDisplayName TargetName A1 A2 A3 A2M_05 A2M 142 48 79 A2M_04 A2M 91 35 60 A2M_02 A2M 131 ...
written 11 days ago by bigitharulesforever0 • updated 11 days ago by Kevin Blighe61k
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Comment: C: How can you use normalised count matrix for differential gene expression analysi
... The normalised data? I also recently got the initial raw counts for this data which has the around 5 probes for each gene which I have summed together. Could I use this to perform a differential expression analysis, if so should I be using limma or EdgeR? I have information regarding which genes ar ...
written 11 days ago by bigitharulesforever0
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Comment: C: How can you use normalised count matrix for differential gene expression analysi
... The file has normalisation method as THIRD_QUARTILE. ...
written 11 days ago by bigitharulesforever0
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Comment: C: How can you use normalised count matrix for differential gene expression analysi
... Thank you Kevin, this is the code I am using. I'm not sure if I am missing any steps. > pacman::p_load(pacman, rio, ggplot2, htmltools, DESeq2, limma, Biobase, GOexpress) > Colorectal <- read.csv("C:/Users/Bigitha/Desktop/allnoc6.csv", row.names = 1) > Colorectal & ...
written 12 days ago by bigitharulesforever0 • updated 11 days ago by Kevin Blighe61k
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How can you use normalised count matrix for differential gene expression analysis?
... Hi, I tried to perform a differential gene expression analysis using Limma for some data that resemble microarray data. They are obtained from nanostring and when I performed the Limma I get logFC values that are in the 100s like -500 etc. I don't know if I am doing something wrong with the data se ...
gene R rna-seq written 12 days ago by bigitharulesforever0 • updated 12 days ago by Kevin Blighe61k

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