User: Alex So

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Alex So0
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Posts by Alex So

<prev • 11 results • page 1 of 2 • next >
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Comment: C: Normalisation for count data visualisation only
... Hello, I thougt about something while sleeping. If I take the data in the **txi$abundance** slot, this will be data without any kind of *« between sample »* normalisation, so the samples cannot be compared together, no ? So the gene comparison is only possible within one sample. Am I right ? (sor ...
written 5 weeks ago by Alex So0
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Comment: C: Normalisation for count data visualisation only
... Hello, So I will extract the TPM values for all my samples to get a matrix of value and use that as an input for the heatmaps and for the clustering. I will also try the things you mentionned here : https://bioconductor.org/packages/release/workflows/vignettes/rnaseqGene/inst/doc/rnaseqGene.html# ...
written 5 weeks ago by Alex So0
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Comment: C: Normalisation for count data visualisation only
... Hello, Thanks you for your answer. I am a bit confused about the definition of gene length bias : What I have in mind when I talk about gene length bias is the fact that longer genes will accumulate more reads and so more count. For example, for a gene of 10kb, I expect him to have 10 times highe ...
written 5 weeks ago by Alex So0
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Normalisation for count data visualisation only
... Hello, Peoples from my lab have been generating some RNA-seq data. I don’t really want to perform differential gene expression analyses on these data. Instead, I want to make some gene profile visualisation, heatmaps, clustering… But no DE analyses. I’ve been using DESeq2 for a long time, but I’m ...
normalization deseq2 salmon tximport written 5 weeks ago by Alex So0 • updated 5 weeks ago by Michael Love23k
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Comment: C: Effectiveness of normalisation if many DE genes using DESeq2
... Tanks a lot, I'm working on the identification of such genes. I have already found some candidates and I tried running deseq2 by including them. I'm doing this : countData <- as.matrix(read.csv("gene_count_matrix.csv", row.names="gene_id")) colData <- read.csv("file_list", sep=",", row.names ...
written 7 months ago by Alex So0
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Comment: C: Effectiveness of normalisation if many DE genes using DESeq2
... Tanks for this answer.   I will look for known housekeeping genes in the literature. If I understand well, It will be possible to improve the normalisation by telling to DESeq2 that "This small list of genes is known to have almost the same level of expression every time" ? My team have charged ...
written 7 months ago by Alex So0
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Comment: C: Effectiveness of normalisation if many DE genes using DESeq2
... Hello, I will try to use RUVSeq. These data have been generated by my team before I arrived, but I think that the only thing we have is the raw reads... So it will be hard to find such control. But if RUVSeq can help it will be good.   Here is the MA-plot of the worst condition (first time point ...
written 7 months ago by Alex So0
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Comment: C: Effectiveness of normalisation if many DE genes using DESeq2
... Thanks for you answer.   I tried to filter the data a bit more based on log2FoldChange. For the timecourse design, if I take genes with l2fc > 1 and those with l2fc < 1 I get 5,000 et 6,000 genes respectively, from 28,000 genes considered differentially expressed. There is a lot of genes wit ...
written 7 months ago by Alex So0
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Comment: C: Effectiveness of normalisation if many DE genes using DESeq2
... Hello michael, tanks you again for you answer, Here are the precisions you asked for.   I have two input files : gene_count_matrix.csv : gene_id,T000A,T000B,T000C,T000D,T012A,T012B,T012C,T012D,…...,T120D,T132A,T132B,T132C,T132D gene_number_1,0,0,0,0,0,3,0,…….,0,0,0,3 gene_number_2,601,431,343 ...
written 7 months ago by Alex So0
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Comment: C: Effectiveness of normalisation if many DE genes using DESeq2
... Hello, thanks for your answer.   I will only be able to give you my code tomorrow, but here are some precisions that may be helpfull.   We are looking at the formation of an organ. The data look Like this :   Rep1 2h Rep2 2h Rep3 2h Rep4 2h Rep1 4h Rep2 4h Rep3 4h Rep4 4h ... Rep1 24h ...
written 7 months ago by Alex So0

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