CLIP-seq protocols combine the action of CLIP (UV Crosslinking and Immunoprecipitation) and NGS (Next Generation Sequencing) to derive a transcriptome-wide set of RBP (RNA Binding Proteins) binding sites. There are different CLIP-seq protocols; each one introduces experimental variations to improve the signal to noise ratio. [1]
In order to process CLIP-seq raw data is important to obtain clusters of sequences. Each cluster contains a set of sequences that overlap at least in one nucleotide, and all the clusters are exclusive. This software obtains the clusters for a CLIP-seq raw dataset; it can filter the resultant dataset by filtering read sequences length, cluster minimum number of reads, entropy (to avoid mononucleotide sequences). Moreover, this tool obtains an experimental prior based on information selected by the user (mutations, deletions).
Information regarding the software requirements, configuration and inputs, usage and outputs are available at follows.
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Created by Carlos Sierra and Paula H. Reyes-Herrera on 30 May 2014 Copyright (c) 2014 Universidad Antonio Nariño. All rights reserved.
CLIP-seq Cluster Detection Tool is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, version 2.
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- Java 1.5 or more
- Minimum 512 Mb of RAM (Recommended 4 Gb of RAM)
- Any processor (Recommended multi-core processor)
- Enough space to save results
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You must to create a set-up file (with extension .ini). In that file write values for parameters required to run the application.
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DataSet=Data set (in SAM format) of reads obtained experimentally.
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Filter_Minimum_Ocurrences=This is a filter to reduce no-significant clusters by have a little number of reads aligned. By default is 5.
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Filter_Minimum_Read_length=This is a filter to reduce no-significant reads by have a little size of sequence. By default is 5.
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Folder_Results=Path where the results will be saved.
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E-mail=Mail to send a message when the experiment is finished.
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FASTA_Folder=Path of FASTA files.
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SNP_Folder=Path of SNP files.
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Export_SAM=Flag to export cluster's list in SAM. By default is FALSE.
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Export_BED=Flag to export cluster's list in BED. By default is FALSE.
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Filter_Entrophy=Flag to use Shannon's Entropy to filter noise reads. By default is TRUE.
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Mutations=Type of mutations to consider (Options:All, T2C, A2C, A2G, A2T, C2A, C2G, C2T, G2A, G2C, G2T, T2A, T2G).
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Insertions=Type of insertions to consider (Options: All, A, C, G, T).
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Deletions=Type of deletions to consider (Options: All, A, C, G, T).
Additional parameters in v1.5:
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Background=Path of background file.
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Background_Score=Filter of minimum read's score value in background to take into account in comparision.
If there are not FASTA files, the application shows a message and does not execute the program. If folder results does not exist, the application will create it.
The setup.ini file (in the same root of this file) is an example of a configuration setup.
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To run, just write on terminal: java -jar ClusterDetection_v*.jar Setup_file_name.ini
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- Total_clusters: List of all clusters (Optionally can be in format .SAM and .BED)
- Filtered_Clusters: List of clusters that pass the filters
- Folders of details of clusters, organized by chromosome
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Created by Carlos Sierra and Paula H. Reyes-Herrera on 30 November 2014 Copyright (c) 2014 Universidad Antonio Nariño. All rights reserved.
CLIP-seq Cluster Detection Tool is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, version 2.