Revealing potential diagnostic gene biomarkers of septic shock based on machine learning analysis

Table 2 28 differentially expressed mRNAs after reducing data dimensions

ID	Symbol	Combined. effect size	P value	False discovery rate	Up/Down
1845	DUSP3	1.966918	< 2.22e−16	< 1.64e−15	Up
3017	HIST1H2BD	1.805068	< 2.22e−16	< 1.64e−15	Up
4257	MGST1	1.871323	< 2.22e−16	< 1.64e−15	Up
5872	RAB13	2.507966	< 2.22e−16	< 1.64e−15	Up
6854	SYN2	1.562134	< 2.22e−16	< 1.64e−15	Up
7378	UPP1	2.807998	< 2.22e−16	< 1.64e−15	Up
8344	HIST1H2BE	1.705221	< 2.22e−16	< 1.64e−15	Up
9759	HDAC4	1.892591	< 2.22e−16	< 1.64e−15	Up
10124	ARL4A	1.554429	< 2.22e−16	< 1.64e−15	Up
10184	LHFPL2	1.50707	< 2.22e−16	< 1.64e−15	Up
23095	KIF1B	2.805012	< 2.22e−16	< 1.64e−15	Up
23601	CLEC5A	2.375364	< 2.22e−16	< 1.64e−15	Up
26502	NARF	1.747345	< 2.22e−16	< 1.64e−15	Up
643332	ECRP	1.947246	< 2.22e−16	< 1.64e−15	Up
404201	WDFY3-AS2	1.551524	< 2.22e−16	< 1.64e−15	Up
1521	CTSW	− 1.56967	< 2.22e−16	< 1.64e−15	Down
2205	FCER1A	− 2.07841	< 2.22e−16	< 1.64e−15	Down
3587	IL10RA	− 1.56804	< 2.22e−16	< 1.64e−15	Down
4603	MYBL1	− 1.74565	< 2.22e−16	< 1.64e−15	Down
6252	RTN1	− 1.74447	< 2.22e−16	< 1.64e−15	Down
9252	RPS6KA5	− 1.70288	< 2.22e−16	< 1.64e−15	Down
9324	HMGN3	− 1.88269	< 2.22e−16	< 1.64e−15	Down
10314	LANCL1	− 1.56694	< 2.22e−16	< 1.64e−15	Down
23370	ARHGEF18	− 1.78719	< 2.22e−16	< 1.64e−15	Down
51348	KLRF1	− 2.74432	< 2.22e−16	< 1.64e−15	Down
55799	CACNA2D3	− 1.58142	< 2.22e−16	< 1.64e−15	Down
83939	EIF2A	− 1.72077	< 2.22e−16	< 1.64e−15	Down
222643	UNC5CL	− 1.51897	< 2.22e−16	< 1.64e−15	Down