Body: <p>I have a matrix of gene expression for single cell (cells in column and genes in row) in 9 time points with about to 200 cells for each time point. I have also a matrix of gene expression in bulk RNA-seq with the same time point and 2 replications. </p>
  
  <p>I have pooled reads from cells in each time point to have a simulated bulk RNA-seq. now I have two matrices; Real bulk RNA-seq in 9 time points and two replication and another matrix a simulated bulk RNA-seq with 9 time points and two replications. I have plotted a heat map of them to show the pattern of gene expression is similar in both matrices so single cell RNA-seq is good enough. Actually I have used the real bulk RNA-seq in a similar study as a gold standard for checking my single cell RNA-seq. My problem is this the pattern of gene expression in 0 time point is very different in two datasets. I should note that 0 time point comes from Fluidigm and another 8 time points come from icell8. I should be able TO adjust this heat map to look similar enough. </p>
  
  <p>So I thought to show similarity by plotting cumulative fraction of genes detectable in varying fractions of cells (lets say 20%, 40%, ...), segregated by bulk RNA-seq expression quartile. Something like a plot that x axis is percent of cells and y axis is percent of genes but I think I should solve the fundamental problem in a heat map.</p>
  
  <p>I have single cell (matrix with T) and bulk RNA-seq (matrix with R). Whatever I am plotting, time point 0 in single cell RNA-seq seems more yellow and dose not allow a good similarity between single cell and bulk RNA-seq. How I can make zero time point less yellow so another time points become more yellow?</p>
  
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2018-07-06T08:35:53.960Z
Comments.Text: How do you rank each cell by number of genes expressed?
Comments.UserDisplayName: llrs
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2018-07-06T09:19:43.983Z
Comments.Text: Thank you, actually I am not sure, if I have FPKM values for bulk RNA-seq, I don't   know how to show how many cells express a quartile of genes in bulk RNA-seq
Comments.UserDisplayName: Zizogolu
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2018-07-06T10:36:10.213Z
Comments.Text: Sorry, I think I misunderstood the question: what has to do the bulk RNA-seq with identifying the variability of genes in **individual** cells? What do you try to show ? You expect that this graph (however it is made) will help you to find/learn that ...?
Comments.UserDisplayName: llrs
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2018-07-06T14:53:49.890Z
Comments.Text: You right the question is very ambiguous,  I want to check similarity of two sets of samples
Comments.UserDisplayName: Zizogolu
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2018-07-06T15:00:32.713Z
Comments.Text: First make sure what you want help with in this question. Then please [edit] the question with more details. Do you want to compare the bulk RNA to the scRNA? Or you want to check the similarity at certain timepoints or between replications?
Comments.UserDisplayName: llrs
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2018-07-06T23:17:21.633Z
Comments.Text: I'm kind of surprised that your method of comparing data from two totally different sample prep methods worked at all, not that it differs significantly at only one timepoint.
Comments.UserDisplayName: swbarnes2
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2018-07-07T11:19:28.270Z
Comments.Text: What do you want? A method to normalize between technologies so that your time point 0 looks more similar between scRNA and bulk or plot the similarity  between bulk and scRNA? Also I assume that this data wasn't corrected by batch/technology effect or it is?
Comments.UserDisplayName: llrs
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2018-07-07T11:26:08.840Z
Comments.Text: I have not done batch correction. I only have pooled 200 cells in each time point to simulate a bulk RNA-seq and I hoped when comparing that with real RNA-seq from the same experiment the data look similar. But likely 0 time point is very different coming from two sequencing methods. after pooling my cells I normalised them with deseq2 like I have done for real bulk RNA-seq. for 8 time points looks good but for zero as this platform gives more read counts. how I manipulate my matrices to make a more similar heat maps or how could I remove difference between 0 time point and another time points
Comments.UserDisplayName: Zizogolu
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2018-07-07T13:09:55.903Z
Comments.Text: Sorry you are right about different sample prep but when I am calculation Pearson correlation between each time point I am seeing a high correlation between data. If this high correlation is by chance? correlation after log transforming both of datasets
Comments.UserDisplayName: Zizogolu
Tags: <r><scrnaseq><transcriptome>
Title: Variability in genes across platforms
ThreadText: # Variability in genes across platforms
  
  (Asked by: username_0 on 2018-07-05)
  
  I have a matrix of gene expression for single cell (cells in column and genes in row) in 9 time points with about to 200 cells for each time point. I have also a matrix of gene expression in bulk RNA-seq with the same time point and 2 replications.
  
  I have pooled reads from cells in each time point to have a simulated bulk RNA-seq. now I have two matrices; Real bulk RNA-seq in 9 time points and two replication and another matrix a simulated bulk RNA-seq with 9 time points and two replications. I have plotted a heat map of them to show the pattern of gene expression is similar in both matrices so single cell RNA-seq is good enough. Actually I have used the real bulk RNA-seq in a similar study as a gold standard for checking my single cell RNA-seq. My problem is this the pattern of gene expression in 0 time point is very different in two datasets. I should note that 0 time point comes from Fluidigm and another 8 time points come from icell8. I should be able TO adjust this heat map to look similar enough.
  
  So I thought to show similarity by plotting cumulative fraction of genes detectable in varying fractions of cells (lets say 20%, 40%, ...), segregated by bulk RNA-seq expression quartile. Something like a plot that x axis is percent of cells and y axis is percent of genes but I think I should solve the fundamental problem in a heat map.
  
  I have single cell (matrix with T) and bulk RNA-seq (matrix with R). Whatever I am plotting, time point 0 in single cell RNA-seq seems more yellow and dose not allow a good similarity between single cell and bulk RNA-seq. How I can make zero time point less yellow so another time points become more yellow?
  
  **Tags:** r, scrnaseq, transcriptome
  
  > **Comments:**
  > **username_1**: How do you rank each cell by number of genes expressed?  
  > **username_0**: Thank you, actually I am not sure, if I have FPKM values for bulk RNA-seq, I don't   know how to show how many cells express a quartile of genes in bulk RNA-seq  
  > **username_1**: Sorry, I think I misunderstood the question: what has to do the bulk RNA-seq with identifying the variability of genes in **individual** cells? What do you try to show ? You expect that this graph (however it is made) will help you to find/learn that ...?  
  > **username_0**: You right the question is very ambiguous,  I want to check similarity of two sets of samples  
  > **username_1**: First make sure what you want help with in this question. Then please [edit] the question with more details. Do you want to compare the bulk RNA to the scRNA? Or you want to check the similarity at certain timepoints or between replications?  
  > **username_2**: I'm kind of surprised that your method of comparing data from two totally different sample prep methods worked at all, not that it differs significantly at only one timepoint.  
  > **username_1**: What do you want? A method to normalize between technologies so that your time point 0 looks more similar between scRNA and bulk or plot the similarity  between bulk and scRNA? Also I assume that this data wasn't corrected by batch/technology effect or it is?  
  > **username_0**: I have not done batch correction. I only have pooled 200 cells in each time point to simulate a bulk RNA-seq and I hoped when comparing that with real RNA-seq from the same experiment the data look similar. But likely 0 time point is very different coming from two sequencing methods. after pooling my cells I normalised them with deseq2 like I have done for real bulk RNA-seq. for 8 time points looks good but for zero as this platform gives more read counts. how I manipulate my matrices to make a more similar heat maps or how could I remove difference between 0 time point and another time points  
  > **username_0**: Sorry you are right about different sample prep but when I am calculation Pearson correlation between each time point I am seeing a high correlation between data. If this high correlation is by chance? correlation after log transforming both of datasets  
  
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  ## 0 answers
  
  