## User: Marina V.V.

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#### Posts by Marina V.V.

<prev • 12 results • page 1 of 2 • next >
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... Hi Aaron, One new doubt has come to me. In the step of gene filtering, when we calculated ave.counts and plot histogram with limit line in 0.1 (in the case of UMIs), you run in your publication: ave.counts <- calcAverage(sce) hist(log10(ave.counts), breaks=100, main="", col="grey",     xlab=exp ...
written 20 months ago by Marina V.V.0
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... You are right. I completely understand and agree with you: we can not decide this threshold because we do not know which is the cause of low expression, and obviously comparisons is what matters. I am now starting with this part :) Thanks so much again! ...
written 21 months ago by Marina V.V.0
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... Thanks!! Just one more doubt: from which level of expression it is considered that a gene is expressed in a cell? I mean, maybe Pvalb>0 is not sufficient because 1 or 5 counts in a cell is not saying that this cell is PV (possible contamination?). So, is there any threshold in count level to sele ...
written 21 months ago by Marina V.V.0
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... Hi again Aaron, I already did the filtering with your recommendations and it works very good! I could finished that part happily, but it came another doubt to me. If you remembered, I need to select only cells with specific expression of one gene inside my sce object and remove the rest. But I can ...
written 21 months ago by Marina V.V.0
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... Thanks a lot, Aaron! I will try this manual filtering, just for total_features or also for percentage of ERCCs and total_counts, to see all possibilities and results. Hope I could find a proper quality control before normalization :) I am very grateful for all your help, sincerely. Thank you very m ...
written 21 months ago by Marina V.V.0
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... I am trying to figure out the problem with the suggestions you made. I found that, after my QC metrics filtering (with nmad=2.5 as I wrote before), the min value for total_features is 1! And the maximum is 6885. I think now the problem is in total_features filtering, right? It seems to me that total ...
written 21 months ago by Marina V.V.0
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... Hi Aaron, Sorry for the split, but the full text did not fit in one post, so I did not see another way to continue writing it. Now I see "ADD COMMENT". Really sorry. I am not a bioinformatic person, so this is all new to me, and I am learning to analyze this data by reading and trying to understand ...
written 21 months ago by Marina V.V.0
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... Continuation 2... In the plot, then, I obtained negative size factors like below and I think that if I do not remove these cells, I will have problems in further analysis (I can not attached the plot, sorry, very big). summary(sizeFactors(sce)) Min. 1st Qu. Median Mean 3rd Qu. Max. ...
written 21 months ago by Marina V.V.0
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... Continuation... As it is recommended in the help for deconvolution methods when to deal with negative size factors, I have tried more restrictive filters for cells (like nmad=2, that I think is the most one) and/or also applied more restrictive gene filter (like average counts >=0.2, 0.5 or 1) a ...
written 21 months ago by Marina V.V.0
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... Hello! I am following the Aaron T Lun et al. 2016 paper to analyze my brain scRNA-seq data, but I am blocked in the step of gene filtering. I have my data in an sce object and I have already filtered outlier cells (isOutlier) and genes based on low-abundance genes (with threshold 0.1 because we used ...
written 21 months ago by Marina V.V.0 • updated 21 months ago by Aaron Lun25k

#### Latest awards to Marina V.V.

Popular Question 19 months ago, created a question with more than 1,000 views. For Error: In seq_len(ncol(assay)) : first element used of 'length.out' argument
Popular Question 19 months ago, created a question with more than 1,000 views. For Warning: negative size factors

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