AgroMarker Finder manual (1.1)

Transcription

1 AgroMarker Finder manual (1.1) 1. Introduction 2. Installation 3. How to run? 4. How to use? 5. Java program for calculating of restriction enzyme sites (TaqαI). 1. Introduction AgroMarker Finder (AMF)is a GUI software for analyzing NGS data, such as RAD-seq and whole genome sequencing. It integrates sophisticated tools with self-developed algorithms that can help users finish data analysis with simple operation. It consists of five independent modules: Filter and Mapping, Bam Convert, SNP InDel Detection and Annotation, Somatic Detection and Variant Location. Depending upon different demands, both integrated functions and a separate feature are available, making the analysis procedure more efficient and flexible. Based on this software, large volumes of polymorphism data have been discovered and analyzed, which will be meaningful for further application, such as genetic mapping, genetic map construction, evolutionary studies and marker-assisted selection. Procedures for data analysis based on AMF are as follows:

2 2. Installation AMF should be built on Linux systems. It is written in Java. To run AMF, users should configure the environment and softwares first. Here are the softwares required: 1. JDK 1.7: html 2. BWA: 3. Bowtie 2: (optional) 4. SAMtools: 5. GATK: 6. Picard: Things to note: BWA, Bowtie 2 (if needed) and SAMtools must be installed on the Linux system path,such as /bin. And you must point out the path of GATK and Picard in SoftwareInfo file. 3. How to run? java jar AMF.jar 4. How to use? 4.1 Filter and Mapping Click button Open to load in the single-end fastq format files to a window on the left or paired-end fastq format files to two windows respectively. For paired-end file, the order of one side in the left-hand window must correspond to another side in the right-hand window. Filtering step and mapping step are independent Filter First, check box FilterReads and choose different parameters. Then, click button SaveTo to select the output file path. Finally, click button Run to start. TrimEndQuality: Raw sequence reads were continuously trimmed from both 3 end and 5 end based on Q value you set. Low quality bases with one base interval could also be recognized and removed. Reads Quality: There are four different standards. In strict standard, low quality reads showing 7 percent bases with Q<10 or 7 percent with Q<13 or 15 percent with Q<20, were discarded. In moderate standard, low quality reads showing 10 percent bases with Q<10 or 14 percent with Q<13 or 20 percent with Q<20, were discarded. In relax standard, low-quality reads showing 15 percent bases with Q < 10 or 20 percent bases with Q < 13, were discarded. If you don t want to filter the reads, you can choose NotFilter. Retain Bp: Only filtered reads up to this length will be retained.

3 LeftAdaptor: Remove the left adaptor sequence of each reads based on the sequence input. RightAdaptor: Remove the right adaptor sequence of each reads based on the sequence input. LowerCase Adaptor: Remove adaptor sequence in lowercase letters. QC Before Filter: Perform FastQC analysis for raw data. QC After Filter: Perform FastQC analysis after filtering. JustQC: Run FastQC analysis only Mapping First, check box Mapping and choose different parameters. Then, click button SaveTo to select the output file path. Finally, click Run to start. Mismatch: Number of mismatch is allowed within all hints. GapLength: Length of gap is allowed within all hints. Species: Species selected for mapping. Rice (Oryza sativa L.) genome information is already provided in AMF. Other species could be added manually: Download FASTA format genome sequence data and GTF file (part of GFF files are also compatible); Create a new folder in the species folder included in the genome folder and arrange the download files according to the existing cases; Fill in SpeciesFile file accordance with the format of the existing cases. NCBI Taxonomy number is suggested for the first column of SpeciesFile (not necessary). Thread: Set the number of threads. Library: Select SingleEnd,PairedEnd, MatePair or MatePairLong based on different sequencing methods. Other parameters of BWA (Burrows-Wheeler Alignment tool) are set by default. You can refer to BWA manual for detailed explanation.

4 4.2 Bam Convert First, click button Open Sam/Bam File to load in Sam or Bam format files. Then, select the needed items. Finally, click ConvertSam to start. If the input file is in Sam format, it will be directly converted to Bam format first. MergeByPrefix: Merge sam or bam files with the same prefix. FilterMultipleMappedReads: Remove multiple mapped reads. If the value of NH or IH flag >1, these reads will be considered as multiple mapped reads. If the bwa-aln tag is XT:R, these reads will be regarded as multiple mapped reads. VCF To Help Recalibrate: Check box Recalibrate Need DBsnpVcf, then input the VCF format file to recalibrate false positive SNPs. Detailed description of each boxes could refer to SAMtools manual or GATK manual. Note: To perform FilterMultipleMappedReads function, user must use the BWA or Bowtie 2 in AMF.

5 4.3 SNP InDel Detection and Annotation Snp/InDel Calling First, click button AddFile to load in pileup format files. Then, set filtering parameter. Finally, click button Run to start. By default, software identifies mutant site with parameters covered by at least 3 reads containing more than 2 mutant reads (different with reference genome), and mutant ratio should exceed 20%. Hetero SNP Reads Prop Level: Input parameter to further filter mutant sites. For example, if you set 0.3. It means more than 30% mutant ratio is necessary to determine the mutant site. Things to note: If the number input is greater than default, the default value will be ignored. Result format: 1. chromosome 2. genome coordinate 3. reference allele 4. alternate allele 5. number of reads showing reference genotype 6. number of reads showing mutant genotype

6 Each columns are split by Tab separator Snp/InDel annotation First, click button AddSnpFile to load in SNP information files in TXT format which should containin four columns respectively recording chromosomes, coordinates, reference alleles and alternate alleles information. Then, select parameters. Finally, click Run button to start. Note: The first line is the default title bar. Col ChrID: Input column number records chromosome. Col SNP Start Site: Input column number records coordinate of alternate allele. Col RefNr: Input column number records reference allele. Col ThisNr: Input column number records alternate allele. Result format: 1. chromosome 2. genome coordinate 3. reference allele 4. alternate allele 5. number of reads showing reference genotype 6. number of reads showing mutant genotype

7 7. Loc number of the gene containing the mutation 8. The location of the mutation on the gene 9. The proportion of the distance of mutation site to the start site of the gene and the length of the gene 10. Normal codon 11. Normal amino acid 12. Mutant codon 13. Mutant amino acid 14. Where does the change of amino acid occur 15. Distance to splice site 16. Changes of physical and chemical properties 4.4 Somatic Detection First, click button OpenSNP to load in SNP format files of two samples generated by Snp/InDel Calling function and click OpenPileUp to load in pileup format files of two samples. Orders need to be kept in same. Then, select parameters and click button SaveTo to select the output file path. Finally, click Run button to start. Species: Select species information. HeteroSNPPropLevel: Input parameter to determine mutant sites as mentioned above. Compare: For control group, sites covered by at least 10 reads, including less than 2 mutant reads (bases different with control group) and less than 4% SNP ratio are kept. For treat group, mutant sites should be covered by at least 3 reads containing

8 more than 2 mutant reads (bases different with reference genome), and mutant ratio should exceed 20%. AMF will record polymorphisms by comparing mutant sites kept in Treat group to Conrol group. Result format: 1. chromosome 2. genome coordinate 3. reference allele 4. alternate allele 5. total number of reads covers this position of sample A 6. number of reads shows mutant genotype of sample A 7. total number of reads covers this position of sample B 9. number of reads shows mutant genotype of sample B 4.5 Variant Location First, click button OpenFile to load in file split by Tab separator recording chromosome and coordinate information. Then, select parameters and click button Run. Finally, click button Save to select the output file path. Note: The first line is the default title bar. PeakRange: Locate the region of mutations. To locate SNPs, you should not check this box. ChrIDColumn: Input column number recording chromosome information.

9 PeakMiddleColumn: Input column number recording the coordinate of the middle site of mutation. PeakEnd Column: Input column number recording the coordinate of the last site of mutation. TSS: Transcription start site (TSS). TTS: Transcription terminate site (TTS). Up: Upstream region from TSS or TTS. - (Minus) must add before the number. Down: Downstream region from TSS or TTS. 5. Java program for calculating of restriction enzyme sites (TaqαI). public class restrictionsite { static long readbpnum = 0; static Set<Long> setpositions = new LinkedHashSet<Long>(); static Pattern pattern = Pattern.compile("TCGA AGCT", Pattern.CASE_INSENSITIVE); public static void main(string[] args) throws IOException { FileReader freader = new FileReader( "/Desktop/Tigr7/chrAll.txt"); BufferedReader breader = new BufferedReader(fReader); FileWriter fwriter = new FileWriter(

10 "/Desktop/ricedigestionnum.txt"); BufferedWriter bwriter = new BufferedWriter(fWriter); String readstring = ""; List<String> lscombineseq = new LinkedList<String>(); String chrid = ""; int posnum = 0; while ((readstring = breader.readline())!= null) { if (readstring.contains(">")) { if (!chrid.equals("")) { for (Long pos : setpositions) { bwriter.write(chrid + "\t" + pos + "\t" + (pos + 3) + "\n"); posnum += setpositions.size(); setpositions.clear(); chrid = readstring.replace(">", ""); readbpnum = 0; lscombineseq.clear(); continue; lscombineseq.add(readstring); if (lscombineseq.size() == 1) { continue; String linkstring = lscombineseq.get(0) + lscombineseq.get(1); List<Long> lspos = Statistic(linkString, readbpnum); lscombineseq.remove(0); readbpnum += 0.5 * linkstring.length(); setpositions.addall(lspos); for (Long pos : setpositions) { bwriter.write(chrid + "\t" + pos + "\t" + (pos + 3) + "\n"); posnum += setpositions.size(); System.out.println(posnum); breader.close(); bwriter.close(); freader.close(); fwriter.close(); public static ArrayList<Long> Statistic(String linkstring, long readbpnumbefore) {

11 ArrayList<Long> posllist = new ArrayList<Long>(); Matcher mat = pattern.matcher(linkstring); while (mat.find()) { posllist.add(readbpnumbefore + mat.start() + 1); return posllist;