Genomatix: Mapping NGS Reads to the small RNA library

Introduction

The Genomatix Mapping Algorithm is used for mapping the input sequences against a small RNA (non-coding RNA) library.

The Genomatix smallRNA library contains 0.25 million sequences of non-coding RNAs collected from a number of pertinent public databases and stratified into 10 classes.
Details and numbers can be found on this page on the small RNA library

The output files of this task (namely the <smallRNA-class>_result.csv-files, see the download section) can be used as input for the Comparative MicroRNA analysis task.

If small RNA sequencing data are mapped to the small RNA library, no linker removal is needed. This speciality is due to the fact that the smallRNA library is constructed in such a way that only the overlaps of the sequence reads with the small RNA is taken into consideration.

Parameters

Input data
Available Files	Input data should contain the input reads / tags from the sequencing. The following formats are accepted: FASTQ format FASTA format color space file format (.csfasta) Within this section you can either choose from previously uploaded Read files or add a new Read file to the list (by clicking "Add Read file...") You can use shift/ctrl-keys to select multiple files from the list. All selected files will then be used as input (also see merge option below). When adding a new file, a new window will open, asking you to either upload one or several Read files from your local computer or import one or several Read files from the GGA (see more details) Note: Paired-end files must be uploaded together to be recognized as paired end! Note that almost all browsers have a general upload limit of 2 GB, i.e. files bigger than this size should be zipped before uploading from your local computer. This restriction does not apply when using the direct import from the GGA. Optionally you can specify a name for saving uploaded files on the server, otherwise the name of the uploaded file will be used. If several files are uploaded, the string given here will be used as prefix for each file name. After one or several Read files were uploaded successfully, and after closing the popup window, the list of available Read files will be automatically updated. Uploaded Read files can be deleted from the project anytime via the project management.
Merge results	If this checkbox is ticked, all mapping results from several input files will be merged into one single BAM output file. Otherwise, each input file will result in a single BAM file which will be stored separately into the result management.
Genomatix Mapper Parameters
Sequencing	Antisense directed Select this checkbox in case of an antisense sequencing experiment (Library type of the RNA-seq protocol.) Specifies whether the strand generated during first strand synthesis (antisense strand) was sequenced. If this option is set, the reads will be reverse complemented before mapping.
Seed Mapping	This parameter controls the seed search strategy: Select fast for an exact search of seeds from the mapping library. Select deep for a seed search with one error tolerance. Note: The seed search mode should be selected according to the sequence length and sequencing error rate. The 'deep' mode should be used if the sequences are short (< 50 bps) or if the expected error rate is high (> 10%). Otherwise the 'fast' mode can be used without losing a significant amount of good hits compared to the deep mode. Note: For smallRNA mapping 'deep' mode is recommended. Please note that for sequences ≥ 75bps this parameter will be automatically set to 'fast'.
Alignment	Alignment type ungapped alignment: Alignment of the complete sequence read to a region in the target sequence, identified via a shortest unique seed is simply done by counting point mutations without consideration of insertions/deletions. gapped alignment: Here, a Needleman-Wunsch alignment is performed, allowing point mutations, insertions, and deletions, e.g. if homopolymer resolution is an issue. Please note that gapped alignment is required for subsequent Small Variant Detection
	Alignment quality can be selected in two different ways: By setting a Minimum alignment quality (0-100%): This parameter determines the minimum overall alignment quality which is reported in the output files. The alignment quality is calculated by the number of aligned nucleotides divided by the overall alignment length. A minimum alignment quality can also be specified via minimum number of allowed point mutations / insertions / deletions (see the following two parameters). If the alignment quality should be specified via minimum allowed numbers of insertions/deletions and point mutations rather than the overall alignment quality, please do not select this option. By setting the Maximum number of allowed point mutations / insertions / deletions: Maximum number of allowed point mutations >= 0: This parameter determines the maximum number of allowed point mutations in the overall alignment which is reported in the output files. Please note that this parameter is only active if the minimum alignment quality parameter is not selected. Maximum number of allowed insertions/deletions >= 0 (only for gapped alignment): This parameter determines the maximum number of allowed insertions/deletions in the overall alignment which is reported in the output files. Please note that this parameter is only active if the gapped alignment ist selected above.
	Note: The choice of the alignment method depends on the sequencer which generated the results: For Illumina (Solexa) sequencers the expected rate of insertions/deletions is very low, therefore the ungapped alignment is sufficient in most cases. Vendors like IonTorrent or 454 should be mapped with gapped alignment due to the inherent rate of insertions and deletions. However, IonTorrent and 454 generally produce sequences of a significant length and therefore these sequences can be mapped in the combination 'fast seed search / gapped alignment'. 92% for Illumina sequences and 85% for SOLID reads have been found to be good hallmarks for the alignment quality parameter.
Masking	These parameters determine the number of base pairs at the ends of the sequence reads which should be excluded from the mapping. Read1 trim 5' Number of base pairs at the 5'end of the sequence reads which should be trimmed. In case of paired end sequencing this parameter refers to the first read. Read1 trim 3' Number of base pairs at the 3'end of the sequence reads which should be trimmed. In case of paired end sequencing this parameter refers to the first read.
Output Options	Reporting of matches: report unique only Only the best unique hit is reported in the resulting BAM file report all incl. multiple hits Here, the algorithm reports also mappings which could be aligned at multiple positions of the target sequence with equal best alignment quality. Note: For smallRNA mapping 'multiple hits' mode is recommended. de novo splicing If this parameter is set, a de novo splice junction detection via spliced alignment of the sequence reads will be calculated. local a local spliced alignment is computed (based on the Genomatix ExonMapper algorithm, see details) global global spliced alignment is performed, i.e. the program searches for splice events in a genome wide manner (details) both both - local and global - spliced alignments are computed
Output
Result	Here, you can edit the default name of the result file.
Email address	Here you can choose between two methods for receiving the results: Show result directly in browser window In this option the URL of the result is directly shown in your browser window. Warning: Please use this option only for analyses which can be performed in a short time. If the analysis takes longer than the timeout of the webserver, the connection will be terminated and you will receive an error message (e.g. "The document contained no data."). In this case, the results will not be available, please restart the analysis using the option below "Send the URL of the result to". Send the URL of the result via email In this option an email with the URL of the results will be sent to the user provided email address, when the analysis is finished. The results will be available for a limited time on our server. For details of how long your results will be kept please see the result-email. After that period they will be deleted unless protected in the project management!

Output

The output has a number of sections, depending on the input and parameters:

Analysis Parameters
Overview
- Mapping Overview
smallRNA Annotation
Hit Distribution
Alignment Quality

Download of Results

The result sections are described in detail below.

1. Analysis Parameters

Name of input read file(s) and selected species and genome build
Result name
Mapping algorithm and version
Further parameters, depending on user selection

2. Overview

Mapping Overview

A table with the main results that were found during mapping. Example:

Here is a description of the categories for the Genomatix Mapper.

3. smallRNA Annotation

The number of reads that map (unique or multiple respectively) to the various small RNA classes are displayed in this view:

The corresponding export file 20_Unique_Hit_Coordinates (see download of files) contains the read ID and the target RNA ID.
Further annotation for each target RNA is also provided in the download section.

4. Hit Distribution

In this chart the Mapping Overview is displayed graphically. Here's an example:

The data is displayed in a pie chart and can either be downloaded in various graphic formats (PNG, JPEG, PDF, SVG) or as tab-separated text file.

5. Alignment Quality

This column chart shows the alignment quality profile for the unique hits and the multiple hits (only if selected in the parameters) respectively.

Example:

The rightmost column shows the number and percentage of perfectly mapped reads (alignment quality = 100). Also shown are the reads mapping with one (alignment quality 97%) or two mismatches. Moving the mouse pointer over one of the columns shows the numbers.
Note that you can zoom into the graphics by selecting a x-range with the mouse. To show the default range, click the "reset zoom" button.

6. Download of Results

All additional files that were created during the mapping process can be downloaded as an archive (tar-file).
For example, if the Genomatix Mapper was started with default parameters the following extra text files are available:

00_Logfile
10_Mapping_Statistics
20_Unique_Hit_Coordinates
30_Multiple_Hit_Coordinates

<smallRNA-class>_result.csv:
listing the total read counts for each small RNA in the library, with genomic positions for all organisms

Broken down into the small RNA classes that comprise the library, these files list the read counts from the unique and multiple alignment. Each line in the file describes one small RNA entity, the number of times it was found in the mapping step and its annotation data including its genomic position.

Format:

Column description	Explanation	Format	Example
Organism	Target organism (three letter format)	String	aga
Chromosome	Chromosome name	String	chr2L
start	start position on chromosome	Int	1385844
end	end position on chromosome	Int	1385865
strand	genomic strand	Char (+/-)	-
GXN	Genomatix ncRNA ID, sequence based	String	GXN_2864
name	ncRNA name	String	mmu-miR-466f-3p
total hits	unique + multiple hits for this ncRNA	Int	321
relative hits	total hits divided by read count for this class	Float	0.00456
annotation	ncRNA annotation	String	mmu-miR-466f-3p MIMAT0004882 Mus musculus miR-466f-3p

For a detailed description of the other files please see the Genomatix Mapper Output section.