Q: What are the system requirements for running PIPseeker?
A: Hardware requirements for running PIPseeker depend on the size and composition of the input data. The requirements scale linearly with the volume of the data, but also depend on the depth of sequencing (sequencing saturation). Higher depth will result in more reads being merged and will reduce the hardware needs.
A good rule of thumb is 2GB of RAM and 10GB of free disk space for every 1 GB of input FASTQ (in .gz format). PIPseeker will perform a system resource (preflight) check prior to starting the analysis and will not continue if it fails. However, as noted above, it is impossible to precisely determine the exact requirements, so PIPseeker may be over- or underestimating the needs. The system check can be skipped using
Note that if you are using a Docker container (directly or via the Windows executable), you will need to make sure that the container is not limited in its access to the machine’s resources. If you are using Docker Desktop, click the Preferences button at the top right, then click “Resources” in the left panel. You should then be able to adjust the allocated RAM and other computing resources.
Tips for reducing memory requirements:
- Reduce the number of PIPseeker threads using
--threads. A value of 1 will completely turn off parallelization (resulting in slower processing).
- Reduce the number of STAR threads using
- Downsample the data using
Q: How do I use PIPseeker on Windows?
A: The Windows PIPseeker executable runs using a Linux Docker container. Therefore, it is required that Docker is installed and running on the same machine. Prior to running PIPseeker, please download and install Docker Desktop, then make sure it is running before you launch the PIPseeker executable.
To run PIPseeker on Windows you will need to use the Windows Command Prompt or PowerShell. In the Start Menu, type “Command Prompt” or “PowerShell” to launch either one of those applications. In the command line, navigate to the folder where you stored the downloaded executable (using the cd command), then type your PIPseeker command. For example:
<C:\path\to\downloaded\pipseeker\>pipseeker-v1.1.7-win-docker-cli.exe full --fastq <C:\path\to\fastq/.> --output-path <C:\path\to\output> --star-index-path <C:\path\to\star\index>
Note that the paths inside angled brackets are placeholders and should be replaced by specific paths on your system. Also, paths that include spaces should be enclosed by double quotes.
Q: How do I use cell type annotation in PIPseeker?
A: PIPseeker can assign cell types to different clusters for some sample types. It requires a cell type annotation reference compatible with the sample. Annotation references are simple CSV format files, and are available to download from the PIPseeker downloads page. Fluent BioSciences is working to expand the range of available sample types for cell type annotation.
To use this feature, download an annotation reference compatible with your sample type, then use the
--annotation option with the full path to the downloaded file. Please see the PIPseeker User Guide for more information.
Q: PIPseeker shows an error message: “System ulimit check failed”
A: This indicates that the operating system’s limit on the number of simultaneously open files is too low. This will cause a failure during STAR’s BAM sorting step. Reduce the number of STAR threads using
--star-threads or increase the system ulimit.
--skip-preflight to skip this check.
Q: PIPseeker fails immediately with ‘GLIBC_2.29’ Error
A: This is typically seen when trying to run PIPseeker on a linux distribution that is not supported. Please check the PIPseeker User Guide for more information.
Q: PIPseeker shows an error message: “R1 has more reads than R2” or “R2 has more reads than R1”
A: This usually occurs when one or multiple fastq files in a set are corrupted. Less commonly, it can be related to issues reading fastqs stored in a cloud bucket.
Q: STAR terminates unexpectedly or PIPseeker shows an error related to a corrupt or missing BAM file.
A: This typically occurs when RAM is exceeded, the disk drive is full, or the number of open files (ulimit) is exceeded.