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The purpose of this pipeline is to aid in the analysis of QTLs in the context of RNA-seq studies. Many softwares of relatively lightweight exist for this purpose, however, the majority are highly specialized to one particular task and many have outputs not suited for immediate use. While it is relatively trivial to run, parse and pipe the outputs of one software to another, it is similarly tedious to do so, especially in data sets of high volume. As such this pipeline consists of a handful of scripts, the purposes of which are to 1) loop software analysis over a large number of subjects and 2) to appropriately parse the outputs of one software for use in another. The flow of analysis is highly predictable, with a moderate level of flexibility for user preferences.
Each section provides a brief example that demonstrates the minimum requirements to run the scripts. For additional options and descriptions, each shell script has its own page describing the options for both the shell script and the r scripts it calls.
- Quality Control
- Sequence Alignment
- Quantification
- QTL Analysis
The sample list follows a fairly simple format.
- There should be no headers
- The first column should be a list of samples
- One sample name per line
- Sample names should not contain any file types (for example .fastq and/or .gz endings can be removed from the name e.g. sample1.fastq becomes sample1)
- Sample names should not contain any path information (for example /home/data/sample1.fastq can be listed as sample1)
- Sample names should not contain any of its end information (For example with paired end files you may have sample1_R1.fastq and sample1_R2.fastq. These may be reduced to simply sample1.)
- The sample list should not contain any duplicates (For example with paired end files you may have sample1_R1.fastq and sample1_R2.fastq. These may be reduced to simply sample1)
Often times the sample names that fastq files are tagged with differ from how they need to be presented downstream. For example, genotype files may contain unique identifiers that differ from the fastq file names. With this in mind it is possible to introduce different names for your samples early on in the pipeline. To do this users can optionally introduce a second column of sample names to the sample list. The first column will still identify the correct input sample and outputs will simply be renamed to match the corresponding name in the second column. This name translation step will only take place during alignment steps. As such if users need to translate names they should do this right from the beginning Users only need to make this list once and it will not interfere with analysis downstream.
an easy and quick way to generate the sample list is using the unix command ls | cut -f 1 -d <delimeter> > sample_list.txt. This will cut file names into chunks that can be easily selected by the user. Please see the cut manual page for more details