You can copy and paste your list of significant feature (gene, metabolite etc) IDs with optional associated p values or fold changes separated by tab. A small example data is shown below (first column: Entrez ID, second column: fold change):

5743	24.25
3552	21.85
6364	14.64
3553	13.07
10148	10.87
6349	9.19
3620	-8.38
50486	-7.25
2919	-6.96
3557	-6.4
629	-6.07
27074	-6.02
                

A small example data using rsID as identifier:

rs1428554
rs41290504
rs3197999
rs516246
rs2228058
                

# SNP
5:140532-140532:1/C

# SNP (reverse strand)
14:19584687-19584687:-1/T

# insertion
1:881907-881906:1/C

# 5bp deletion
2:946507-946511:1/-
                

You can copy and paste your list of significant taxon names with optional associated abundance separated by tab. A small example data is shown below (first column: Genus name, second column: abundance):

Parabacteroides	47376.29
Roseburia	44882.80
Ruminococcus	1384440.62
Staphylococcus	6372.25
Streptococcus	15792.09
Sutterella	31861.25
unclassified_Clostridiales	9973.95
unclassified_Erysipelotrichaceae	399789.43
unclassified_Lachnospiraceae	674350.30
unclassified_Pseudomonadaceae	1939.38
                

• For taxon names, if there is a space (" ") in the name (i.e. unclassified Clostridiales) replace space with "_" (unclassified_Clostridiales).
• If there are unclassified taxa in your data of the query taxonomy level, you can use the term “unclassified_” plus the parent taxonomy for estimation. e.g.: f__Lachnospiraceae; g__; will be “unclassified_Lachnospiraceae” in the input box.

Supported file formats: .graphml, .sif, .json or .txt file containing edge list. For more information, please read our FAQs or download example files below.

Supported formats: .csv or .txt, including four columns [m/z, RT, intensity and p value]. For more information, please read our FAQs or download example files below.