Hello, we have some pilot data that we are trying to run through the pipeline and <1% of the total fastq_reads are assigned as fastq_valid_barcode_reads. We know that this is not an issue our ability to run the pipeline because we have successfully run test data from the original publication. To troubleshoot, we have already confirmed that the experiment we ran was with v1 chemistry and it matches the v1 barcodes in the pipeline.
The only remaining difference between our data and the test data is the average read length. We sequenced to 121nt for both R1 and R2, could this be the source of the invalid reads? I noticed in "tools_debug.py" the 8nt bc positions are defined by an absolute position. Do you have a suggestion for improving detection of the correct position?
Hello, we have some pilot data that we are trying to run through the pipeline and <1% of the total fastq_reads are assigned as fastq_valid_barcode_reads. We know that this is not an issue our ability to run the pipeline because we have successfully run test data from the original publication. To troubleshoot, we have already confirmed that the experiment we ran was with v1 chemistry and it matches the v1 barcodes in the pipeline.
The only remaining difference between our data and the test data is the average read length. We sequenced to 121nt for both R1 and R2, could this be the source of the invalid reads? I noticed in "tools_debug.py" the 8nt bc positions are defined by an absolute position. Do you have a suggestion for improving detection of the correct position?