I have a salmonella treated vs KD condition , i want something like this but I not sure how linear regression can be done  

    Gene	SCRSAL1	KDSAL3
    CXCL1	10.8273907686	11.2751328718
    CXCL2	8.001064472	8.5753884341
    CXCL3	8.1965832765	8.7086794002
    CXCL5	8.0973357585	8.6242736829
    CXCL6	9.9053940183	10.8940613053
    CXCL8	13.1127454083	13.4402538026
    CXCL10	7.2590758038	7.8202130661
    CCL20	9.0933584064	9.9218889828
    CCL22	7.3643976273	7.7911788897
    CCL28	8.3723507486	8.6786344048
    IL36G	4.3423919715	4.5673548181

This is my dataset the kind of figure i m trying is this ![enter image description here][1]
Any suggestion or help would be highly appreciated 


  [1]: https://i.imgur.com/72t9hkq.png
With perfect data, if you plot gene levels for knockdown vs control, any gene above the 45˚ line is upregulated in the knockdown compared to control, the farther away from the line, the stronger the effect. A linear regression will help in dealing with imperfect data. To help decide on which genes are upregulated, you can calculate (and plot) a confidence interval on each side of the regression line.
For how to do this in R, see this [Rstudio notebook][1].


  [1]: https://rpubs.com/aaronsc32/regression-confidence-prediction-intervals