Click on "Run the Pipeline" to start the analysis. The input mask will look like this: Every request is associated with a unique ID number. All running processes have their specific ID and are handled in order of the submission time. The last 10 request IDs are displayed in "Previous Runs / Views" on the left side menu. One can see the previously run processes either via this list, or by entering the request ID in "ID" field of the input mask.

Notes

• The calculation of the results may take minutes up to hours. As long as the calculation is in process, you are redirected to a "waiting" page. It updates automatically every minute. Nevertheless, you can close the "waiting" page. Nanopipe will send you an email (if previously entered) when the calculations are finished (remember your request ID!).
• Requests are kept for 30 days on the server. After this period all the data will be deleted.
• There is a limit of 100 open requests. That means that if you try to submit your data and there are 100 requests running, you will have to wait until the queue is ready to accept requests again.
• The maximum size of a query is 3GB.

Some targets are already prepared and displayed in the Target selection box. If you want to provide your own target, you can upload your file.

The query is your data and always a file (in fastq or fasta format). You can only submit ONE file at a time. To send several files in one request, you can archive them together and send the archive file. Archive formats are zip. To archive files do this (in general - in Unix)

zip archive.zip file1 file2 ...

or use a Windows tool like WinZip. Then you can upload the file archive.zip to Nanopipe and proceed.

Note: Transfer and calculation times will generally increase when sending big files.

Enter the minimum length of the query reads which should be analyzed. We recommend the minimum length of 100, but it depends on your data and aim of the experiment.

Enter an email address to receive a notification when your job is completed.

The substitution matrix and the fields "Match Score" and "Mismatch Cost" are mutually exclusive - meaning that you can only use one of them. If you do not enter values (meaning empty or "0") into the substitution matrix, you can select "Match Score" and "Mismatch Cost" fields. Otherwise they are invisible.

When the request is finished, the main results page will be displayed first: You have the option to select a specific results page, presented on the header line (upper menu). Some of the results pages are target name dependent: It is first required to select a particular chromosome/contig name of the target by clicking "First Select" before browsing through.

The Mapping Distribution displays the number of reads (Nreads) that have been mapped per target.

The Query Distribution displays the distribution of the length of the queries. Note: The graph may have a last bar which sums up counts bigger then a specific length - this works as follows: Try to find the length from start where 95% of all counts are occupied. From this point go further to the right and look if the longest length is at least twice as much as this 95% length. If so, sum up all length together in ONE bar, otherwise display the lengths as they are.

The Alignment Distribution displays the number of reads (Nreads) with a particular alignment length (i.e., the part of the read that has been mapped) per target.

The nucleotide plots display the distribution of the four nucleotides along the target In the upper section you see colored bars. On the Y axis the reads number is printed, on the X axis - the position in the target. Vertical lines indicate a "gap" in the target position, meaning that the read coverage at this position is less than 10. It is possible to navigate along the graph using the menu below it. You may move to the left or to the right, or enter an exact target position. With "BarWidth" you can change the size of the displayed bars. At the bottom of the Nucleotide Plot page there is an overview graph of the plot, so you can easily find the positions with better coverage. Just click on the alignment pick at the overview graph and the colored nucleotide plot will move to the desired location.

The polymorphisms table contains the information about putative single nucleotide polymorphisms (SNP) in the analyzed sequence. Candidates fulfill three requirements:

1. The coverage of the target nucleotide is lower than or equal to 80 % of the total coverage at that position. This can be adjusted by setting the "Target threshold" during job submission. A low value will set the focus on regions which are less conserved between your query and the target. A high value will also include more conserved positions, as well.
2. For non-target nucleotides at that position: The coverage must be greater than or equal to 20% of the total coverage. This can be adjusted by setting the "Polymorphism threshold" abundance during job submission. Low values will result in calls of low- and high-frequency SNPs. A high value will result in calls of only high-frequency SNPs.
3. A position on an individual target must have a certain coverage relative to the maximum coverage of the individual target. An individual target may, for example, be a chromosome of your target genome. By default, positions must have a coverage of 30% of the individual target's maximum coverage. E.g.: Chromosome 1 has a maximum coverage of 3000. Thus, positions on chromosome 1 need to have a minimum coverage of 1000.

   You can change the default by adjusting the "Coverage threshold" during job submission. Lower the value to include also low-coverage positions. Increase the value to exclude low-coverage positions.

After this filtering step, the remaining SNPs are weighted. For that, the relative occurrence of each base at the given position is calculated. Then, the changes from the target nucleotide to the observed nucleotide are evaluated. The assumption here is that transitions are twice as likely as transversions. The weighted occurrence of each nucleotide shows the likelihood of observing a nucleotide different from the target.

1) The algorithm provides additional information for each SNP candidate from dbSNP for Homo sapiens and from PlasmoDB for Plasmodium falciparum. If matching entries are found, the corresponding IDs and other available information are added to the output.

Note: For human data we use the novel API of dbSNP which allows for searches on a valid chromosome. Non-valid chromosomes include chrM and chromosomes ending with further comments, like: chr1_mycomment. Non-valid target sequences are indicated by N/A in the respective output column. db:error indicates that the attempt to connect with dbSNP has failed.

2) As another additional feature, the alignment quality is being analyzed: The p-value is calculated based on the LAST alignment quality values. The average p-value for the region of 10 bases before and 10 bases after the candidate SNP is estimated. The interpretation of this value may be following:

1. The SNP lays in a region of low alignment quality. Therefore, it is likely reflecting a sequencing error and not a biological pattern.
2. The SNP lays in a SNPs cluster and this reciprocally affects the alignment quality.

The output will look similar to the following example: The rows of the table include the following information:

1. Position: The position of the SNP candidate.
2. A, C, G, T: The joint probabilities of the SNP being an A, C, G or T (see above).
3. Target: The nucleotide in the target.
4. Matches in dbSNP/Matches in PlasmoDB: For dbSNP: [rs-IDs: alleles] are reported for the position. db:error indicates a failed try to contact dbSNP. For PlasmoDB: [ID: major allele: frequency + minor allele: frequency] are reported. No entry means no match, N/A indicates that a chromosome is not in the databases (see above). The SNP data base data are currently only provided for the two species: H. sapiens and P. falciparum. For any other target types, this column is missing.
5. P-error (local alignment quality): The average p-value around a SNP (see above).
6. raw A, raw C, raw G, raw T: Raw coverage observed for A, C, G and T.

The consensus of the sequenced DNA or RNA is provided. It is generated based on the majority rule, i.e. the nucleotide with the highest count at a particular position is being assigned to the consensus sequence at this position. If a nucleotide has coverage of less than 10, a gap is introduced. If the nucleotides' coverages at a position are similar (within 80% similarity), NanoPipe uses the IUPAC nomenclature to acknowledge this uncertainty, see IUPAC code.

Note: in the consensus sequence "X" stays for any of the four nucleotides, and "N" meaning that there were not enough data to make a decision.

The pairwise alignment of consensus and target sequences is displayed here.

We generate .bam and .bai files for you, so you could visualize the results in IGVviewer (see Broadinstitute). The FASTA file with the corresponding target sequence is also available for download, as it is required for IGVviewer.