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Then using the command plink --file fA --merge-list allfiles. In this case, the file allfiles. The --merge-mode option can also be used with the --merge-list option, as described above: Extract a subset of SNPs: Based on a single chromosome --chr To analyse only a specific chromosome use plink --file data --chr 6 Based on a range of SNPs --from and --to To select a specific range of markers that must all fall on the same chromosome use, for example: The --snps command will accept a comma-delimited list of SNPs, including ranges based on physical position.
For example, plink --bfile mydata --snps rsrs,rsrs,rs,rs selects the same range as above rs to rs but also the separate range rs to rs as well as the two individual SNPs rs and rs Note that SNPs need not be on the same chromosome; also, a range can span multiple chromosomes the range is defined based on chromosome code order in that case, as well as physical position, i.
No spaces are allowed between SNP names or ranges, i. Based on physical position --from-kb , etc One can also select regions based on a window defined in terms of physical distance rather than SNP ID, using the command: HINT Two alternate forms of the --from-kb command are --from-bp and --from-mb that take a parameter in terms of base-pair position or megabase position, instead of kilobase to be used with the corresponding --to-bp and --to-mb options.
One must combine this option with the desired analytic e. The format of myrange. For example, if the SET file genes. One must combine these options with the desired analytic e. As described above, the --range command can modify the behaviour of --exclude in the same manner as for --extract.
Make missing a specific set of genotypes To blank out a specific set of genotypes, use the following commands, e. HINT See the section on handling obligatory missing genotype data, which can often be useful in this context. Extract a subset of individuals To keep only certain individuals in a file, use the option: Remove a subset of individuals To remove certain individuals from a file plink --file data --remove mylist. Filter out a subset of individuals Whereas the options to keep or remove individuals are based on files containing lists, it is also possible to specify a filter to include only certain individuals based on phenotype, sex or some other variable.
The basic form of the command is --filter which takes two arguments, a filename and a value to filter on, for example: The filter can be any integer numeric value. As with --pheno and --within , you can specify an offset to read the filter from a column other than the first after the obligatory ID columns.
Use the --mfilter option for this. For example, if you have a binary fileset, and so the FAM file contains phenotype as the sixth column, then you could specify plink --bfile data --filter data.
Because filtering on cases or controls, or on sex, or on position within the family, will be common operations, there are some shortcut options that can be used instead of --filter.
These are --filter-cases --filter-controls --filter-males --filter-females --filter-founders --filter-nonfounders These flags can be used in any circumstances, e.
Attribute filters for markers and individuals One can define an attribute file for SNPs or for individuals, see below that is simply a list of user-defined attributes for SNPs. For example, this might be a file snps. Not all SNPs need appear in this file; SNPs not in the dataset are allowed to appear they are just ignored ; the order does not need to be the same. Each SNP should only be listed once however. A SNP can be listed by itself without any attributes for example, to ensure it is not excluded when filtering to exclude SNPs with a certain attribute, see below.
To filter SNPs on these, use the command combined with some other data generation or analysis option --attrib snps. To exclude SNPs that match the attribute, preface the attribute with a minus sign on the command line, e. Finally, multiple filters can be combined in a comma-delimited list --attrib snps.
If a SNP does not feature in the attribute file, it will always be excluded. For example, matching on A,B,-C,-D implies individuals with A or B and not C or D This approach works similarly for individuals, except the command is now --attrib-indiv , e. F1 1 sample2 F2 1 sample1 F3 1 sample2 fullinfo The command --make-set-border takes a single integer argument, allowing for a certain kb window before and after the gene to be included, e. Rather, it can be used anywhere that --set can be used, to make sets on the fly.
Similar, --set and --write-set can be combined, e. Options for --make-set To collapse all ranges into a single set i. Sets can be constructed which collapse over these groups. Normally, the fifth column will just be ignored, unless the command --make-set-collapse-group is added, which creates sets of SNPs that correspond to each group i.
The command --make-set-complement-group works in a similar manner, except now forming sets of all SNPs not in the given group of ranges. Tabulate set membership for all SNPs It is possible to create a table that maps SNPs to sets, given a --set file has been specified, with the --set-table command, e. This format can be useful for subsequent analyses i.
These can be used to filter on user-defined thresholds. The command --qual-scores indicates the file containing the scores. Scores are assumed to be numbers between 0 and 1, a higher number representing better quality. The threshold at which SNPs are selected can be set with the command --qual-threshold. The additional flag --qual-max-threshold can be used to specify a maximum threshold also i. The file containing the genotype quality scores should have the following format: Q fam1 ind1 rs 0.
Not all genotypes need be in this file. Rather than have a very large file, one could only list genotype scores that are below some threshold, for example, assuming most genotypes are of very good quality. Genotypes not in the this file will be untouched.
This format is designed to accept wildcards, as follows. Consider this example file, Q A 1 rs 0. Here's how to read from a file on disk using the StorageFile class. The common first step for each of the ways of reading from a file is to get the file with StorageFolder.
Then use a DataReader object to read first the length of the buffer and then its contents. Open a stream for your file by calling the StorageFile. It returns a stream of the file's content when the operation completes. Get an input stream by calling the GetInputStreamAt method. Put this in a using statement to manage the stream's lifetime. Specify 0 when you call GetInputStreamAt to set the position to the beginning of the stream. Leave blank to use the default encoding on your system.
On first use, Spoon will search your system for available encodings. Allows you to specify the type of compression,. Only one file is placed in a single archive. Add spaces to the end of the fields or remove characters at the end until they have the specified length.
Improves the performance when dumping large amounts of data to a text file by not including any formatting information. If this number N is larger than zero, split the resulting text-file into multiple parts of N rows.
The fields tab is where you define properties for the fields being exported. The table below describes each of the options for configuring the field properties:. The format mask to convert with. See Number Formats for a complete description of format symbols.
The trimming method to apply on the string. Trimming only works when there is no field length given. Alter the options in the fields tab in such a way that the resulting width of lines in the text file is minimal. So instead of save , we write 1, etc.
String fields will no longer be padded to their specified length. All fields of this step support metadata injection. You can use this step with ETL Metadata Injection to pass metadata to your transformation at runtime.
Which is kind of annoying, as files could rotate based on name changes such as Add But when initially each file is created it should write a header. Although a footer is more complicated. Pentaho Data Integration Steps. A t tachments 0 Page History. Description The Text file output step is used to export data to text file format. Options File Tab The File tab is where you define basic properties about the file being created, such as: Option Description Step name Name of the step. This name has to be unique in a single transformation.
Filename This field specifies the filename and location of the output text file. Run this as a command instead? Pass output to servlet Enable this option to return the data via a web service instead writing into a file see PDI data over web service Create parent folder Enable to create the parent folder Do not create file at start Enable to avoid empty files when no rows are getting processed. Accept file name from field?
Enable to specify the file name s in a field in the input stream File name field When the previous option is enabled, you can specify the field that will contain the filename s at runtime. Extension Adds a point and the extension to the end of the filename. Include partition nr in filename?
Includes the data partition number in the filename. Include date in filename Includes the system date in the filename.