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Fast, Accurate, and Complete SSR Detection in Genomic Sequences
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README ====== Table of Contents ----------------- I. Introduction II. Installation Instructions III. Usage Instructions and Examples IV. Funding and Acknowledgements V. Contact I. Introduction --------------- Kmer-SSR is a software tool developed to find Simple Sequence Repeats (SSRs) in a sequence (presumably of DNA or RNA). SSRs are sometimes referred to as Short Tandem Repeats (STRs) or microsatellites. SSRs are genetic markers with several interesting and meaningful biological implications. For example, SSRs can play significant roles in genome alignment against a reference and species identification. Many software tools exist for this purpose, but vary widely in utility. Some key features of our tool are as follows: - Fast run time (linear, O(n), time complexity) - Memory efficient (linear, O(n), space complexity) - Finds all perfect repeats - Simple command-line interface, convenient for scripting and when running on High-Performance Computing (HPC) systems (note: no GUI provided) - Easily parsed, tab-delimited output - Runs on Linux (not Windows or Mac OS X) See our paper in __journal__ for further information: http://sub.domain.tld/path/to/resource II. Installation Instructions ----------------------------- To compile Kmer-SSR, simply type `make'. The binary will be in the `bin' directory. Your compiler must support C++11. To compile and install, type `make' followed by `make install'. The binary will be in both the `bin' and `/usr/local/bin' directories (to change this, change the `PREFIX' variable in `Makefile'). To uninstall, type `make clean'. See `INSTALL' for further instructions. III. Usage Instructions and Examples ------------------------------------- Please run the software with the `--help' option for complete usage instructions (i.e., type `kmer-ssr -h' or `kmer-ssr --help'). The format of the input and output files is described below; followed by usage examples. Input File Format: Description: The input file must be in Fasta format. The sequences may be on a single line or multiple lines. The header and sequence lines must not contain any leading or trailing whitespace. The header line must not contain any tabs. The sequence lines must not contain whitespace between nucleotides. Mixed-case nucleotides are acceptable; they will be replaced with uppercase nucleotides for finding SSRs. Good Example: >sequence 1 AGCGTGTCGTGTACACGTGTACGTACGTACGATCGATGCTACGTAGCATCGATCGACGTATCGTATCGATC CACGTGTACGTACGTACGATCGATGCTACGTAGCATCGATCGACGTATCGTATCGATCAGCGTGTCGTGTA . . . >sequence 2 cgtacgatcgatgctacgtagcatcgatcgacgtatcgtatcgatcagcgtgtcgtgtacacgtgtacgta gatcgacgtatcgtatcgatcagcgtgtcgtgtacacgtgtacgtacgtacgatcgatgctacgtagcatc . . . >sequence 3 taTCgATCAGCGtGTCGTGTAcACGTGTACGTAcgtaCGAtCgATGCTACGTagcatCGATCGACGTATCG cgtacgtacgATCGATGCTACGTaGCATCGaTCGaCGTAtCGTAtcgatcaGCGTGTCGTGTAcacgtgta . . . Output File Format: Description: The output file is tab-delimited. Each row is a separate record. By default, if no SSRs are found in a fasta sequence, no output record will be present in the output file for that fasta sequence. When SSRs are found, one output record will be present in the output file for each SSR in that sequence. Each column contains a separate piece of information for the output record. The columns (in order) are: Sequence_Name, SSR, Repeats, Position (zero-based) Each of the columns are described below: Sequence_Name: The entire header line from the fasta file (excluding the leading `>' character) from which the SSR in the given output record is found. SSR: The repeating unit of an SSR. For example, `ACACAC' is an SSR with a repeating unit of `AC'. Repeats: The number of times the repeating unit of an SSR repeats. For example, the repeating unit of `AC' from SSR `ACACAC' repeats 3 times. Position: The zero-based position in the original fasta sequence where the SSR begins. For example, `ACACAC' begins at position 2 in the sequence `TGACACACGT'. As a simple illustration of the output file, consider the following input file and its respective output file: Input: >seq 1 TGACACACGT >seq 2 acgtg tgtca cagtc Output (formatted here for readability): Sequence_Name SSR Repeats Position (zero-based) seq 1 AC 3 2 seq 2 GT 3 2 seq 2 CA 2 8 Usage Examples: Basic Usage Examples: Example 1: kmer-ssr -i input.fasta -o output.tsv Run Kmer-SSR on fasta sequences in `input.fasta' and write results to `output.tsv'. This will use the default parameters; run the software with `--help' to see the defaults and check if they meet your needs. Example 2: kmer-ssr -p 2-9 -r 3 -R 20 -i input.fasta -o output.tsv Run Kmer-SSR on fasta sequences in `input.fasta' and write results to `output.tsv'. Only SSRs meeting the parameters provided will be included. The meaning of each option is as follows: -p Search for SSRs with a period size of 2, 3, 4, 5, 6, 7, 8, or 9. As examples: `AAAAAA...' and `ACGCAGTTGCACGCAGTTGC...' would not make the cutoff because `A' is shorter than 2 nucleotides and `ACGCAGTTGC' is longer than 9 nucleotides. However, `ACACAC...' and `AATCCTGGTAATCCTGGT...' would be included. -r, -R The min (-r) and max (-R) times the repeating unit repeats. As examples: `ACAC' and `ACACACACACACACACACACAC ACACACACACACACACACAC' (21 `AC' units) would not make the cutoff. However, `ACACAC' and `ACACACACACACACACACACACACAC ACACACACACACAC' (20 `AC' units) would be included. Example 3: kmer-ssr -t 4 -i input.fasta -o output.tsv Run Kmer-SSR on fasta sequences in `input.fasta' and write results to `output.tsv'. Use 4 threads of execution, instead of the default 1. Example 4: kmer-ssr -p 2-9 -r 3 -R 20 -t 4 -i input.fasta -o output.tsv Run Kmer-SSR on fasta sequences in `input.fasta' and write results to `output.tsv'. This is a combination of examples 2 and 3. Extended Example: The data for this extended example can be found in the `examples' directory. The input fasta file is `input.fasta'. The output files are `output_default.tsv' and `output.tsv'. The data and example are fictitious, but was modified from real sequences. The numbers used for min/max sequence length or any other parameter may not be biologically realistic; however, they do conceptually represent a realistic situation. input.fasta: Each fasta sequence is a contig generated from a de novo assembly of whole exome sequencing reads. The file has 16 fasta sequences. output*.tsv: The output files from running Kmer-SSR as shown below. One could just run Kmer-SSR with the defaults: kmer-ssr -i input.fasta -o output_default.tsv However, the defaults may not be the best parameters for your data. Below is a reasonable command to use with this example data. Each alteration from the default is explained and justified based on the data in this example. kmer-ssr -l 70 -L 300 -p 2-9 -r 2 -t 4 -f -i input.fasta -o output.tsv -l 70 Do not search for SSRs in fasta sequences less than 70 bps in length. For sake of the example, we assume based on our reads and the assembler's parameters and intricacies that the resulting contigs should be equal to or longer than 70 bps. Anything shorter would be erroneous and not worth searching for SSRs. -L 300 Do not search for SSRs in fasta sequences more than 300 bps in length. For sake of the example, we assume based on our reads and the assembler's parameters and intricacies that the resulting contigs should be equal to or shorter than 300 bps. Anything longer would be erroneous and not worth searching for SSRs. -m 2 Do not report SSRs where the base unit is less than 2 bps in length. This decision must be made based on your research question(s) and what you deem biologically interesting. -M 9 Do not report SSRs where the base unit is more than 9 bps in length. This decision must be made based on your research question(s) and what you deem biologically interesting. -r 2 Do not report SSRs where the base unit repeats less than 2 times. This decision must be made based on your research question(s) and what you deem biologically interesting. -t 4 Use 4 threads of execution instead of the default 1. This must be based on the machine you run Kmer-SSR on. Obviously, it doesn't make sense to run with 9 threads on an 8 thread machine. -f Output the full sequence from the fasta file from which an SSR in a particular output record was found. This may be desirable if your downstream analysis requires knowing the full sequence from which the SSR was found. This option is intended to ease downstream analysis by removing the requirement to parse the original fasta file and the output file simultaneously. If you do not need this, do not use this option as it will radically increase the size of the output file. If you inspect these two output files, you'll observe 12 output records in `output_default.tsv' and 7 output records in `output.tsv'. Using the custom parameters removed 6 output records; each were theoretically erroneous results (the SSRs really were there in the fasta sequence, but the fasta sequence wasn't valid). 1 additional output record was added by using the custom parameters because the fasta sequence was below the minimum length for processing under the default parameters. IV. Funding and Acknowledgements ------------------------------- Funding for the research and production of this software was provided by startup funds to Dr. Perry Ridge. V. Contact ----------- For questions, comments, concerns, feature requests, suggestions, etc., please contact: Pery Ridge, Ph.D. -- email@example.com Note: For usage questions, please consult section `III. Usage Instructions and Examples' first.