[GenoMax]

Let us know if using more memory made a difference.

You should really be using a different tool designed for long read alignments. Even LASTZ may be appropriate since you have query sequences as long as 7.5Mb.

[Grammatonotus]

a colleague suggests that the mapper may have come to a read that hits too many places in the reference. I have it set to place this at Random, would changing to First Best, None, or All be likely to give a different result?

Also wondering if setting maxlen=4000 might change anything. I don't know how diverged the two are so kind of just guessing really. Thanks.

[Grammatonotus]

When I run it locally about 52 Gb (I ran out of system memory when I had it set to 58), on the cluster 439 Gb. I hope that's not the problem!

[GenoMax]

@grammtonotus: How much memory are you allocating for this job? With that large sized fragments you are likely going to need plenty.

I also suggest that you look into using `minimap2` from Heng Li as an alternate option to BBMap.

[Grammatonotus]

A little bit more information: the DNA sequence in the error message maps to the middle of a contig about 2.8 Mb, starts 402,000 bases in. I tried running this both locally and on a cluster and got the same error message with almost exactly the same sequence in each-- 2045 bases in one, 2205 bases in the other, with ~99% overlap. Any insights appreciated.

[Grammatonotus]

shredding and mapping long reads to reference error

Hello,

I have a reference and I have an additional genome sequenced via 10x that contains 150k contigs from 1k to 7.5Mb. I am attempting to align the second to the first with BBMap by using the flag maxlen=2000 as there are extensive rearrangements. This morning I found this error message. Can anyone tell me what might have happened? Thanks.

'BBMap failed with error code 1
Executing align2.BBMapPacBio [maxlen=2000, maxindel=4000, ambiguous=random, k=15, saa=f, maxlen=6000, minratio=0.40, minscaf=100, startpad=10000, stoppad=10000, midpad=6000, ref=ref.fasta, out=bbmap.sam, in=reads1.fasta]

BBMap version 37.64
Set MINIMUM_ALIGNMENT_SCORE_RATIO to 0.400
Choosing a site randomly for ambiguous mappings.
Writing reference.
Executing dna.FastaToChromArrays2 [ref.fasta, 1, writeinthread=false, genscaffoldinfo=true, retain, waitforwriting=false, gz=true, maxlen=536670912, writechroms=true, minscaf=100, midpad=6000, startpad=10000, stoppad=10000, nodisk=false]

Set genScaffoldInfo=true
Writing chunk 1
Writing chunk 2
Writing chunk 3
Writing chunk 4
Writing chunk 5
Writing chunk 6
Writing chunk 7
Set genome to 1

Loaded Reference: 0.007 seconds.
Loading index for chunk 1-7, build 1
No index available; generating from reference genome: /Users/wilfordbrimley/Geneious Prime/temp/17/ref/index/1/chr1-3_index_k15_c2_b1.block
No index available; generating from reference genome: /Users/wilfordbrimley/Geneious Prime/temp/17/ref/index/1/chr4-7_index_k15_c2_b1.block
Indexing threads started for block 0-3
Indexing threads started for block 4-7
Indexing threads finished for block 0-3
Indexing threads finished for block 4-7
Generated Index: 249.271 seconds.
Analyzed Index: 71.551 seconds.
Started output stream: 0.096 seconds.
Cleared Memory: 0.195 seconds.
Processing reads in single-ended mode.
Started read stream.
Started 24 mapping threads.
Exception in thread "Thread-29" java.lang.AssertionError: -30, -30
89764, 2,0,149134394,149142098,0,00,971,475770,460506,0,389847,149134394~149139756~149140058~149142098,mmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmSmmmmmmmmmmmmmmmmmmmmmmSmmmmmmmmmmmmmmmmmSmmmmmmmmmmmmmmmmSmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmSmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmSmmmmmmmmmmmmmmmmmmmmmmmmmSmmmmmmmmmmmmmmmmmmmmmmSmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmSmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmSmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmSmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmSmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmSmmmmmmmmmmmmmmmmmmmSmmmmmmmmmmmmmmmmmmmmmSmmmmmmmmmmmmmmmSmmmmmmmmmmmSmmmSmmmmmmmmmmmmmmmmmmmmmmmmSmmmmmmmmmmmmmmmmmmmSmmmmmmmmmmSmmmmmmmmmmmmmmmSmmmmmmmmmmmmmmmmmmmmmmmmmmSmmmSmmmmmmmmmmmmmmmSm
...
GCATTCAGACAAGGGTAGCAATATCAATCAACTCTATCTGCTTACAGGAATTGAGCTAGCATAAAGTGCTAAACTCATACTATCAGGCATAACCTAGTCAGGCTATCCTACTTACTGTCTACTCAATATAGGGGTGAGCATTTGGACCGGTGGACCGGACCGGACCGGTGAACCGGACCGGACCGAACCGGATCGGACCGTTTTTTTGGACCCCCGGGCCGGTTCTCGGTTCTAAGATTTCTCGCCGGCCCGGTCTGGTTTTTTTCCCGGTCCGGTCCGGTTTTTACCGGGTTTAGAACCGGTTGGACATGATTAAGATTTTTGTGACGTTTTTTAAACGCACATAACTCATTTGTTTTAAGTTGGATTGACCTGCGGTTTTTCCAACATTTAGTTTACAATTTGTAGATGAATTTAGACTATAATTTTGTTTATTTTGGTATTATATTCACCGTGTTACAATCCTTCAAAGTAGACCTAACAAAGCTGAAAAAATTCAGTTTTTCAGCAACATTTTGTAAGCTGTGACGTTTTTTAAACATCCATAACTCATTCGTTTTAATTCGGATTGACCTCCGATTTTTTCCAACATTTAGTTTACAGTTTGTAGATGAGTTTAGACTATAATTTTGTTTATTTTGGTATTATATTCACTGAGCTACAATCCTTTAAAGTAGAGCTATCAAAGTTGAAAAAATTTAGCTTTTTAGCAAAATTTTATAATCTGTGACGTTTTTTAAACACCCATAACTCATTCGTTTTAAGTTGGATTGACCTACGGTTTTTTCCAACATTTAGTTTACAATTTGTAGATGAATTTAGACTATAATTTTGTTTATTTTGGTATTATATGCATTGAGTTACAATCCTTCAAAGTAGAGCTATCAAAGCTGAAATATTTCAGCTTTTTAGTATTATTTTATACTATAATCCCGAGTCCGCGTTTAGCACTTGTGGTAGAGTTGTAAGTGAGTATCAAACTAGTTTATCGACATTGATAGTTGAAGCTTTGTTATGCACCCAAGATTGGGTGATAAAGTTTACAAATCCGATAGTTGACAACGTTGGTGACATCTTGAACGATGATGATATAACTTTGGGTAAAAAAATTACAATCTTTATTCTTTTTTTATACAATTATTACTTTTTATTAAATACTAACAACATTTTCATTTGTGTTTATGTAGAGATTGCACAAGCTTTAAATATGTTACATATGGATGACAATGATATGGGGAAGAGGCCAATAGAAGATTAGATTATGAGTTTATGAAATTTGTTAGTTTGATTGATTTTAAAGTTTAAACTATGATTTTTGTTGTTACGGTAATACTTTTGTATGTTTGTCTTAAAATTGTTTAACTTTTGTTGGTGAACTTGATTTATATGTTAGTTGCTTTTATTTGGAAAATTAATTTTTGCAAATTGCAAGTTATAATATTATACATCAATGTAGATTAGTTAGGCATGAAACGGAAACATATTAATTTTGCAAGTTATAATATTATACATCAATGTAGATTACTTATTATACTCTATGCAATTAAAGTTGTACCGGTCCAAACGAGTCCAAAAACCGGAAAACCCGGACCTAGACCCGGACACGGACACGGACACGGACACGACTAATCCGGTCCGGTCCATGGTCCACAAAATTCTCCATAGCCGGTCCGGTCCGATTCGGTCCGGGCCTGTCCAAATGCTCACCCCTAACTTAATATCTAGCATGCAATTCTTATACAACTGAAACACATAAAGCAGGCACATAAGGCATCACTCCTAGATCCTTAGTCCTATTCTAGCATGCTGTTCTACAAAAGCTGATAAACATAACATAAACTTGTAAGGGTACTTTGGGGAATACTTACTTGAGCTCGGCCGGTCGCGCACATCACACACTTCGTTCTTTCTCGAAACTCTTTTCTTAGTTTTTTAGAAAACATTTTCTTTTTAGAAAATCTTTTAATCCCTTGATTTGAGTTCAGACACCCCCGAAGGTGTGTCCGAATCCCTCAAACCAGGGCTCTGATACCAACTTGTAACGACCCAAATTTCACGTTCAAAAATTTCGTTTTAAAATGTTACTTTAGAAAACATTAATAATTAAAACATTGTTTGATCAAACCATAACACAACGTAAACCATGTCTAAAAGCCAAATCACACAACCAATCAAACATCAGAGTATAAAACCCAAAGAATCTCG
at align2.MultiStateAligner9PacBio.makeGref(MultiStateAligner9PacBio.java:1388)
at align2.MultiStateAligner9PacBio.fillLimited(MultiStateAligner9PacBio.java:96)
at align2.TranslateColorspaceRead.realign_new(TranslateColorspaceRead.java:565)
at align2.TranslateColorspaceRead.realign_new(TranslateColorspaceRead.java:641)
at align2.AbstractMapThread.genMatchStringForSite(AbstractMapThread.java:1006)
at align2.AbstractMapThread.genMatchString(AbstractMapThread.java:902)
at align2.BBMapThreadPacBio.processRead(BBMapThreadPacBio.java:563)
at align2.AbstractMapThread.run(AbstractMapThread.java:502)
Detecting finished threads: 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23

**************************************************************************
Warning! 2 mapping threads did not terminate normally.
Check the error log; the output may be corrupt or incomplete.
Please submit the full stderr output as a bug report, not just this message.
**************************************************************************




------------------ Results ------------------

Genome: 1
Key Length: 15
Max Indel: 4000
Minimum Score Ratio: 0.4
Mapping Mode: normal
Reads Used: 581616 (2969452913 bases)

Mapping: 177826.639 seconds.
Reads/sec: 3.27
kBases/sec: 16.70


Read 1 data: pct reads num reads pct bases num bases

mapped: 81.2921% 472808 78.5245% 2331747518
unambiguous: 76.0459% 442295 75.7328% 2248849209
ambiguous: 5.2462% 30513 2.7917% 82898309
low-Q discards: 12.7684% 74263 15.0015% 445463533

perfect best site: 4.9337% 28695 4.2346% 125743838
semiperfect site: 5.0009% 29086 4.2700% 126794871

Match Rate: NA NA 84.9205% 2173341879
Error Rate: 87.8894% 442044 13.2182% 338289025
Sub Rate: 84.8676% 426846 1.8940% 48472068
Del Rate: 67.4695% 339341 8.8901% 227520440
Ins Rate: 68.5198% 344624 2.4342% 62296517
N Rate: 30.3789% 152792 1.8614% 47637054
Exception in thread "main" java.lang.AssertionError:
The number of reads out does not add up to the number of reads in.
This may indicate that a mapping thread crashed.
If you submit a bug report, include the entire console output, not just this error message.
238640+234168+0+34543+74263 = 581614 != 581616
at align2.AbstractMapper.printOutputStats(AbstractMapper.java:1892)
at align2.AbstractMapper.printOutput(AbstractMapper.java:1022)
at align2.BBMapPacBio.testSpeed(BBMapPacBio.java:462)
at align2.BBMapPacBio.main(BBMapPacBio.java:37)
'

[SDH]

Hello

My sequencing output largely consists of Illumina (NextSeq and Miseq) NON-overlapping paired end reads (the occasional reads will overlap, as the DNA is not all fragmented evenly). For ease of storage and to simplify input data at the start of a workflow, I would like to combine the files.

If I understand correctly, bbmerge is specifically for merging overlapping reads? In which case I am best off simply using the bbmap reformat.sh to combine the reads in to one interleaved file?

reformat.sh in1=read1.fq in2=read2.fq out=reads.fq

[darthsequencer]

Is there a multi-sample pileup? I have a bunch of samples mapped to the same reference. It would be awesome to have that as a table with the coverage for each sample per reference sequence.

[GenoMax]

While BBMap is not originally designed for this purpose; I made a version that does a much better job at finding all mappings above some identity threshold, bbmapskimmer.sh. The usage is the same as BBMap; just add the ambig=all flag.

Does this mean that bbmap functions identically but does not report all the alignments in the output file but includes them in the statistics for alignment?

[Brian Bushnell]

Hi guys,

I'm trying to get bbmap to find all hits up to some identity threshold for a 20bp read, but it only finds the perfect hit. This should be possible right? So I must be doing something wrong.

While BBMap is not originally designed for this purpose; I made a version that does a much better job at finding all mappings above some identity threshold, bbmapskimmer.sh. The usage is the same as BBMap; just add the ambig=all flag.

[Brian Bushnell]

Hi Brian, I have a problem whereby I have a about 12 fastq files and I'm not completely convinced that the barcode for each of the samples are as named in the key. If I have 12 unique 6-mer barcodes eg GTCCGC, etc is there a way to definitively say which samples have the following barcode with bbmerge? thanks!

BBMerge might be able to help in this case, if you have paired reads with a sufficient number of short inserts. You can run it like this:

bbmerge.sh in1=read1.fq in2=read2.fq outa=adapters.fa

This will indicate the adapter sequence for the library, based on read-through from short-insert reads. The barcode is typically part of the adapter, so if you compare the adapters from 2 multiplexed libraries, the location where they differ is the barcode region.

[GenoMax]

I assume you are referring to a standard barcode/index from Illumina tech. If so those are never part of actual read. If they are present in the fastq header then you could use "demuxbyname.sh" to separate the reads you are interested in.

If your index is "inline" (and at a specific location in the read e.g. beginning) then you could use bbduk.sh to match/separate those reads.

I am not sure bbmerge.sh is going to help in your case.

[Alex Lee]

Hi Brian, I have a problem whereby I have a about 12 fastq files and I'm not completely convinced that the barcode for each of the samples are as named in the key. If I have 12 unique 6-mer barcodes eg GTCCGC, etc is there a way to definitively say which samples have the following barcode with bbmerge? thanks!

[milan.molbio]

Yeah I've come to terms with the fact that BBMap wasn't really designed for this type of use. When I want to work with an alignment strategy where the goal is to find "all" alignments of a read up to some maximum error threshold I turn to bowtie (1 or 2) or BWA.

i did give them both a try. bowtie seems to reliably find and report them but it's got a limit of maximum 3 mismatches (and I need 4 bwa is also struggling to find all the matches, and i've filed an issue: https://github.com/lh3/bwa/issues/176

[sdriscoll]

Yeah I've come to terms with the fact that BBMap wasn't really designed for this type of use. When I want to work with an alignment strategy where the goal is to find "all" alignments of a read up to some maximum error threshold I turn to bowtie (1 or 2) or BWA.