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Don't cat paired and unpaired reads. For Megahit, you need to use the -r flag, like this:
Code:megahit --12 paired.fq -r singletons.fq
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I am also looking for programs/ scripts that would allow me to combine both the merged and orphaned PE reads into one file to use for assembly via Megahit. Any suggestions?
I tried to cat the files together and megahit rejected the file with the output 'number of paired-end files not match!'.
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The output files should be in your working directory, the same directory as the input files. What do you get when you run "ls *.f*"?
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Thank you for the advice Brian. I am trying out bbtools (bbduk and bbmerge).
I just got bbduk to run, but now I can't find the output files on my system . . . do I have to have existing directories to accept these files?
Below is the command I just ran:
bbduk.sh in1=1_ATGAGGCCAC_L007_R1_001.fastq in2=1_ATGAGGCCAC_L007_R2_001.fastq out1=1_cleanR1.fq out2=1_cleanR2.fq ref=/data/laura/Extracted_Metagenomes/bbmap/resources/adapters.fa ktrim=r k=23 mink=11 hdist=1 tpe tbo
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Originally posted by lwebs View PostI am using the illumina-utils program to quality filter reads before de-novo assembly with the iu-filter-quality-minoche flag (see here for more info: https://github.com/merenlab/illumina-utils).
So far, approximately 68% of both R1 and R2 pass the QC parameters while 32% fail (94% percent of failures due to R2).
Here are my questions: Is this error rate and magnitude for read 2 normal
Consulting your link:
C33: less than 2/3 of bases were Q30 or higher in the first half of the read following the B-tail trimming
Should I quality filter the reads prior to merging some of the reads (if only about 20% can be merged)?
Also, BBMerge can merge non-overlapping reads, if you have high enough coverage; this is useful in this kind of scenario where only 20% of the reads overlap due to a large average insert size.
Can I use both merged reads and unmerged R1 and R2 for de novo assembly using Megahit?
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Quality-filtering shotgun metagenomic sequences from environmental samples advice
Hello all!
I am analyzing illumina Hiseq4000 - generated paired-end shotgun metagenomic sequences obtained from environmental samples. I am also new to shotgun metagnomic data, but have had experience analyzing 16S data.
The reads are 150 nt in length and a majority of the fragment sizes range from 280-700 bp. A few samples have fragment sizes ranging from 80- 600 bp.
I am using the illumina-utils program to quality filter reads before de-novo assembly with the iu-filter-quality-minoche flag (see here for more info: https://github.com/merenlab/illumina-utils).
So far, approximately 68% of both R1 and R2 pass the QC parameters while 32% fail (94% percent of failures due to R2).
Here are my questions: Is this error rate and magnitude for read 2 normal?
Should I quality filter the reads prior to merging some
of the reads (if only about 20% can be merged)?
Can I use both merged reads and unmerged R1 and R2
for de novo assembly using Megahit?
Thanks for the help!
Any guidance would be appreciated!
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