Is there a maximum number of reads able to be loaded into tophat

[will.jackson]

Hi everyone,
I am currently mapping some RNAseq reads back to a reference genome I have generated. I did a test run the other day with half of my data (three biological replicates of one cell type) and 60,053,663 of the left reads were kept (2518 discarded) and 36,130,330 of the right reads were kept (20,491 discarded). When I started the run yesterday with my full set of samples (2 different cell types with 3 biological replicates each) I found that the same amount of reads were kept and discarded as when I was only using half my data set. Does anyone know why this is happening?

Here is how I submitted the job:

tophat -r 146 --mate-std-dev 23 -I 5000 --coverage-search /home/willj/02_291012_bwt2/ref/cell_79_St /home/willj/02_291012_bwt2/sample1_RNAseq/DG_H1_ACTTGA_L001_R1_001_T_Q.fastq,/home/willj/02_291012_bwt2/sample1_RNAseq/DG_H1_ACTTGA_L001_R2_001_T_Q.fastq /home/willj/02_291012_bwt2/sample1_RNAseq/DG_H2_GATCAG_L001_R1_001_T_Q.fastq,/home/willj/02_291012_bwt2/sample1_RNAseq/DG_H2_GATCAG_L001_R2_001_T_Qf.fastq /home/willj/02_291012_bwt2/sample1_RNAseq/DG_H17412_TGACCA_L001_R1_001_T_Q.fastq,/home/willj/02_291012_bwt2/sample1_RNAseq/DG_H17412_TGACCA_L001_R2_001_T_Q.fastq /home/willj/02_291012_bwt2/sample2_RNAseq/DG_S12412_ATCACG_L001_R1_001_T_Q.fastq,/home/willj/02_291012_bwt2/sample2_RNAseq/DG_S12412_ATCACG_L001_R2_001_T_Q.fastq /home/willj/02_291012_bwt2/sample2_RNAseq/DG_S18112_CGATGT_L001_R1_001_T_Q.fastq,/home/willj/02_291012_bwt2/sample2_RNAseq/DG_S18112_CGATGT_L001_R2_001_T_Q.fastq /home/willj/02_291012_bwt2/sample2_RNAseq/DG_S22312_TTAGGC_L001_R1_001_T_Q.fastq,/home/willj/02_291012_bwt2/sample2_RNAseq/DG_S22312_TTAGGC_L001_R2_001_T_Q.fastq

Thanks very much

[will.jackson]

Silly error

Hi,
After thinking about my how I loaded up the sequences over the weekend, I realised I had made a really silly mistake and loaded the reads in pairs and not comma delimited left reads then comma delimited right reads. Such a n00b. Sorry for wasting everyone's time.

Cheers,
Will