Frequently Asked Questions (FAQs)
  1. Is the data that I uploaded kept confidential?
  2. What types of data does NetworkAnalyst accept?
  3. How many samples can I upload for an analysis?
  4. How to label a gene expression table?
  5. How to format a gene expression table?
  6. What if my microarray platform or organism is not supported?
  7. How to prepare network files for NetworkAnalyst?
  8. What are the advantages of registering an account?
  1. Is the data that I uploaded kept confidential?

    Yes. The data files you upload for analysis as well as any analysis results, are not downloaded or examined in any way by the administrators, unless required for system maintenance and troubleshooting. All files will be deleted automatically after 72 hours, and no archives or backups are kept unless you have registered an account and saved the analysis. You are advised to download your results immediately after performing an analysis.

  2. What types of data does NetworkAnalyst accept?

    NetworkAnalyst accepts data from 17 species, in the following formats:

    1. List(s) of genes or proteins: one or more lists of gene or protein IDs with optional expression profiles (i.e. fold changes). Each gene should be in a row. Please refer to our example data for more details.
    2. Single gene expression data table: a data table containing expression values (i.e. gene/probe intensities from microarray, counts from RNA-seq saved as a tab delimited text file (.txt) with rows for features (genes/probes) and columns for samples. The tab delimited file can be generated from any spreadsheet program. More details are provided in the following sections.
    3. Multiple gene expression tables: gene expression data from multiple studies collected under similar conditions can be integrated in a meta-analysis.
    4. Network file: users can upload network files generated with a different software to perform network visualization in NetworkAnalyst. More details on network file formats are provided in the corresponding questions below.
    5. Short-read RNA-Seq fastq files: users can upload single or paired-ends RNA-Seq fastq files and perform quality checking, trimming, mapping using well-established Galaxy pipeline. Please note, as the task can not be complete in real time, (free) registration required - users will need to provide a valid email in order to retrieve the result later.
  3. How many samples can I upload for an analysis?

    There is a 50MB limit for the uploaded data. For gene expression profiles with 20 000 genes, this corresponds to about 300 samples. Note - since DESeq2 requires high computational resources, there is a 50 sample limit for this option.

  4. How to label a gene expression table?

    It is critical to properly label your data so that they can be recognized and compared. The following common IDs are supported:

    1. Gene ID: Entrez ID, Ensembl Gene ID, GenBank Accession ID, RefSeq ID, Ensembl Transcript ID, and official Gene Symbol
    2. Probe ID (for human, mouse and rat only): popular microarray plotforms from Affymetrix, Agilent, Illumina;

    The gene expression data also should contain sample names in the first line. Each sample name should be unique. The class labels of experimental conditions should be in a new line beginning with "#CLASS". Multiple class labels can be indicated by adding a colon and its name (for example, "#CLASS:cancer_type" and "#CLASS:stage"). For meta-analysis, the same set of labels must be used for ALL datasets.

  5. How to format a gene expression table?

    Here is a good tutorial on how to generate tab delimited text files from the Excel Spreadsheet program. When you open your data using any text editor (for example, WordPad), it should look like the following:

    • Sample name, one class label (one missing value)
          #NAME	Sample1	Sample2	Sample3	Sample4	Sampl5	Sampl6	Sample7	Sample8
          #CLASS	case	case	case	case	control	control	control	control
          Gene1	-3.06	-2.25	-1.15	-6.64	0.4	1.08	1.22	1.02
          Gene2	-1.36	-0.67	-0.17	-0.97	-2.32	-5.06	0.28	1.32
          Gene3	1.61	-0.27	0.71	-0.62	0.14		0.11	0.98
          Gene4	0.93	1.29	-0.23	-0.74	-2	-1.25	1.07	1.27
                                          
    • Sample name, two class labels (cancer and sex)
          #NAME           Sample1	Sample2	Sample3	Sample4	Sampl5	Sampl6	Sample7	Sample8
          #CLASS:CANCER	case	case	case	case	control	control	control	control
          #CLASS:SEX	F	F	M	M	F	M	F	M
          Gene1           -3.06	-2.25	-1.15	-6.64	0.4	1.08	1.22	1.02
          Gene2           -1.36	-0.67	-0.17	-0.97	-2.32	-5.06	0.28	1.32
          Gene3           1.61	-0.27	0.71	-0.62	0.14		0.11	0.98
          Gene4           0.93	1.29	-0.23	-0.74	-2	-1.25	1.07	1.27
                                          
  6. What if my microarray platform or organism is not supported?

    You have three options:

    1. Keep the ID Type as "Not Specified". You can still perform statistical analysis (differential expression, meta-analysis, volcano plot, heatmap, etc);
    2. Use the microarray annotation file to annotate probes to one of the common gene IDs that are supported (entrez, refseq, ensemble, etc)
    3. It is possible to add support for other model organisms/platforms based on user requests. Feel free to send us your suggestions. Note, this could take a while depending on the available time.

  7. How to prepare network files for NetworkAnalyst?

    NetworkAnalyst support four different types of files (.sif, .txt(edge list), .graphml and .json).
    Please click on the following links to see example files supported:

  8. What are the advantages of registering an account?

    Registering on NetworkAnalyst allows you to save up to 10 projects that will be stored in the system for 10 months. You will be able to reload the work state of previous projects to resume previous analysis.

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