<p>I m not sure if I'm going the right way or not but when the gene and region and both upregulated in RNA seq and ATAC seq data I should be seeing  a positive correlation but it seems other wise.</p>
<p>Am i doing it in a wrong way or this can occur?</p>
<p><a href="https://i.sstatic.net/DjMut.png" rel="nofollow noreferrer"><img src="https://i.sstatic.net/DjMut.png" alt="plot" /></a></p>
<p>Adding the scatter with points</p>
<p><a href="https://i.sstatic.net/rHEfI.png" rel="nofollow noreferrer"><img src="https://i.sstatic.net/rHEfI.png" alt="scatter " /></a></p>
<p><strong>Updated Plot</strong></p>
<p>But the issue is with the R^2 value it is very low
<a href="https://i.sstatic.net/YTmXX.png" rel="nofollow noreferrer"><img src="https://i.sstatic.net/YTmXX.png" alt="updated plot" /></a></p>

CC BY-SA 4.0
2021-01-11T01:08:01.730Z
this looks like amazing results if true. How many data points do you have? can you add that to the plot or do a heatscatter ?
StupidWolf
CC BY-SA 4.0
2021-01-11T05:41:40.940Z
1400 UP region and genes ..I okay I will add scatter "this looks like amazing results if true." Im confused..
kcm
CC BY-SA 4.0
2021-01-11T05:52:36.143Z
@StupidWolf updated the plot
kcm
CC BY-SA 4.0
2021-01-11T06:18:24.853Z
this looks really weird.. did you flip the direction of the fold change.. and was the data subsetted somehow
StupidWolf
CC BY-SA 4.0
2021-01-11T06:28:43.903Z
Bit of background ..I did LRT test with HSC(Stem cell) as my reference level Then compared it to the rest of the Cell type which is Myeloid Progenitor,Leukemic stem cell, Monocyte ,Blast. So my idea was to see how the global changes happens across the normal and malignant cell types. So is the comparison is logical?
kcm
CC BY-SA 4.0
2021-01-11T06:29:39.327Z
"did you flip the direction of the fold change." ..even if that happens would it change ?like if RNA fold change is changed to ATAC or vice versa?
kcm
CC BY-SA 4.0
2021-01-11T07:03:14.827Z
if i go by this paper  figure 2 the fold changes are my figure looks similar except the slope  https://epigeneticsandchromatin.biomedcentral.com/articles/10.1186/s13072-019-0260-2/figures/2
kcm
CC BY-SA 4.0
2021-01-11T07:20:47.770Z
For ATAC seq what i did is..if i have multiple regions annotated to gene i take the average of the region and then did the this fold change scatter
kcm
CC BY-SA 4.0
2021-01-11T07:22:33.063Z
now looking at the dataframe looks like i made some blunder, " and was the data subsetted " this was the error
kcm
CC BY-SA 4.0
2021-01-11T09:07:28.753Z
the last plot looks about right. most likely you need to subset on genes that are more highly expressed (because the range of the fold change looks crazy), and maybe try promoters for a start
StupidWolf
CC BY-SA 4.0
2021-01-11T11:33:20.903Z
"and maybe try promoters for a start" will do that
kcm
<rna-seq><atac-seq>
ATAC and RNA seq Up regulated region gene and scatter
# ATAC and RNA seq Up regulated region gene and scatter

(Asked by: username_0 on 2021-01-09)

I m not sure if I'm going the right way or not but when the gene and region and both upregulated in RNA seq and ATAC seq data I should be seeing a positive correlation but it seems other wise.

Am i doing it in a wrong way or this can occur?

[![plot](https://i.sstatic.net/DjMut.png)](https://i.sstatic.net/DjMut.png)

Adding the scatter with points

[![scatter ](https://i.sstatic.net/rHEfI.png)](https://i.sstatic.net/rHEfI.png)

**Updated Plot**

But the issue is with the R^2 value it is very low
[![updated plot](https://i.sstatic.net/YTmXX.png)](https://i.sstatic.net/YTmXX.png)

**Tags:** rna-seq, atac-seq
> **Comments:**
> **username_1**: this looks like amazing results if true. How many data points do you have? can you add that to the plot or do a heatscatter ?  
> **username_0**: 1400 UP region and genes ..I okay I will add scatter "this looks like amazing results if true." Im confused..  
> **username_0**: @StupidWolf updated the plot  
> **username_1**: this looks really weird.. did you flip the direction of the fold change.. and was the data subsetted somehow  
> **username_0**: Bit of background ..I did LRT test with HSC(Stem cell) as my reference level Then compared it to the rest of the Cell type which is Myeloid Progenitor,Leukemic stem cell, Monocyte ,Blast. So my idea was to see how the global changes happens across the normal and malignant cell types. So is the comparison is logical?  
> **username_0**: "did you flip the direction of the fold change." ..even if that happens would it change ?like if RNA fold change is changed to ATAC or vice versa?  
> **username_0**: if i go by this paper  figure 2 the fold changes are my figure looks similar except the slope  https://epigeneticsandchromatin.biomedcentral.com/articles/10.1186/s13072-019-0260-2/figures/2  
> **username_0**: For ATAC seq what i did is..if i have multiple regions annotated to gene i take the average of the region and then did the this fold change scatter  
> **username_0**: now looking at the dataframe looks like i made some blunder, " and was the data subsetted " this was the error  
> **username_1**: the last plot looks about right. most likely you need to subset on genes that are more highly expressed (because the range of the fold change looks crazy), and maybe try promoters for a start  
> **username_0**: "and maybe try promoters for a start" will do that  

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## 0 answers

