bioinfo.pipeline.Pipeline

Pipeline object to build and run end-to-end bioinformatics analyses and workflows

Since R2023a

Description

The bioinfo.pipeline.Pipeline object lets you construct and execute bioinformatics pipelines and workflows to analyze genomic data.

Creation

Create the object using bioinfo.pipeline.Pipeline.

Properties

Blocks — Blocks in pipeline

vector

Blocks in the pipeline, specified as a vector of block objects.

BlockNames — Names of blocks in the pipeline

string vector

Names of the blocks in the pipeline, specified as a string vector.

Object Functions

addBlock	Add blocks to pipeline
blockName	Return the names of specified blocks in pipeline
cancel	Cancel blocks in pipeline that are running in parallel
compile	Verify pipeline structure and check for warnings and errors
connect	Connect two blocks in pipeline
copy	Copy array of handle objects
deleteResults	Delete block results from pipeline
disconnect	Remove connection between ports in a pipeline
fetchResults	Wait for parallel-running block to finish and return its results
findBlock	Get block objects from bioinformatics pipeline
inputNames	Get names of unconnected block inputs from pipeline
portMap	Show connected ports between two blocks
processTable	Return information about all processes in pipeline
removeBlock	Remove blocks from pipeline
renameBlock	Rename block in pipeline
results	Get bioinformatics pipeline results
run	Run pipeline
wait	Wait for running blocks to complete

Examples

Create a Simple Pipeline to Plot Sequence Quality Data

Import the Pipeline and block objects needed for the example.

import bioinfo.pipeline.Pipeline
import bioinfo.pipeline.block.*

Create a pipeline.

qcpipeline = Pipeline;

Select an input FASTQ file using a FileChooser block.

fastqfile = FileChooser(which("SRR005164_1_50.fastq"));

Create a SeqFilter block.

sequencefilter = SeqFilter;

Define the filtering threshold value. Specifically, filter out sequences with a total of more than 10 low-quality bases, where a base is considered a low-quality base if its quality score is less than 20.

sequencefilter.Options.Threshold = [10 20];

Add the blocks to the pipeline.

addBlock(qcpipeline,[fastqfile,sequencefilter]);

Connect the output of the first block to the input of the second block. To do so, you need to first check the input and output port names of the corresponding blocks.

View the Outputs (port of the first block) and Inputs (port of the second block).

fastqfile.Outputs

ans = struct with fields:
    Files: [1×1 bioinfo.pipeline.Output]

sequencefilter.Inputs

ans = struct with fields:
    FASTQFiles: [1×1 bioinfo.pipeline.Input]

Connect the Files output port of the fastqfile block to the FASTQFiles port of sequencefilter block.

connect(qcpipeline,fastqfile,sequencefilter,["Files","FASTQFiles"]);

Next, create a UserFunction block that calls the seqqcplot function to plot the quality data of the filtered sequence data. In this case, inputFile is the required argument for the seqqcplot function. The required argument name can be anything as long as it is a valid variable name.

qcplot = UserFunction("seqqcplot",RequiredArguments="inputFile",OutputArguments="figureHandle");

Alternatively, you can also use dot notation to set up your UserFunction block.

qcplot = UserFunction;
qcplot.RequiredArguments = "inputFile";
qcplot.Function = "seqqcplot";
qcplot.OutputArguments = "figureHandle";

Add the block.

addBlock(qcpipeline,qcplot);

Check the port names of sequencefilter block and qcplot block.

sequencefilter.Outputs

ans = struct with fields:
    FilteredFASTQFiles: [1×1 bioinfo.pipeline.Output]
         NumFilteredIn: [1×1 bioinfo.pipeline.Output]
        NumFilteredOut: [1×1 bioinfo.pipeline.Output]

qcplot.Inputs

ans = struct with fields:
    inputFile: [1×1 bioinfo.pipeline.Input]

Connect the FilteredFASTQFiles port of the sequencefilter block to the inputFile port of the qcplot block.

connect(qcpipeline,sequencefilter,qcplot,["FilteredFASTQFiles","inputFile"]);

Run the pipeline to plot the sequence quality data.

run(qcpipeline);

Version History

Introduced in R2023a