While I of course never have stupid mistakes...ahem...I have many "friends" who:
- forget to check both strands
- generate random genomic sites without avoiding masked (NNN) gaps
- confuse genome freezes and even species
but I'm sure there are some other very common pitfalls that are unique to bioinformatics programming. What are your favorites?
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Jeremy Leipzig
78 answers
Invent a new weakly defined, internally redundant, ambiguous, bulky fruit salad of a data format. Again.
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biobot 0.0.77.a.1099
This still makes me laugh every time I read it...and cry a little inside too.
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Daniel Standage
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Daniel Standage
It made me laugh when I read the MIQE guidelines not long after this comic came out:
The nomenclature describing the fractional PCR cycle used for quantification is inconsistent, with threshold cycle (Ct), crossing point (Cp),and take-off point (TOP) currently used in the literature ... we propose the use of quantification cycle (Cq)
It's funny because it's true :D
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ebrown1955
I truncated many fasta files this way when trying to see which headers it contained:
grep > some.fasta
I also see a lot of off-by-one errors due to switching between formats
- Bed is 0 based
- GFF/GTF are 1-based
and switching between languages:
- Python and nearly every other modern language are 0-based indexing
- R is 1-based (as is Lua)
Not only is the bed format 0-based, it's also "half-open", meaning the start position is inclusive, but the end position is not.
So if your region starts at position 100 and ends at 101 using standard 1-based coordinates with both start and end inclusive (ie it's two bases long), when you convert it to 0-based half-open coords for bed format the region now starts at 99 but it still ends at 101!
Yeah, the people who conceived of that were utterly brilliant usability specialists.
YES, THAT IS an interesting feature when, as a bioinformatican, you're working with C-arrays , you want to define an empty interval, an insertion point, etc..
You should also have told the correct command:
grep '>' some.fasta
And yes, of course, I did this before as well :D
Gene annotation stored in an excel file and find out that some HUGO gene names have been hacked by Excel. SEPT9 become sept-9. Conclusion Do not use the .xls format to store your data.
Listen people saying this eternal mistake "Hey these two sequences are 50% homologs"
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Fred Fleche
This is a popular one, dec1 is another well known example. But you can actually tell Excel not to do that auto correction. Since you most often get the data from biologist who may have treated the data in Excel already better use an another ID column and not the gene name column if that is available (you often receive both anyway). These errors can even occur in databases that you download data from or which are used for annotation, so it is good to check.
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Chris Evelo
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Simon Cockell
@Simon Thanks for the publication
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Fred Fleche
Uh oh. Looks like something was lost here in the migration.
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Daniel Standage
"Hey these two sequences are 50% homologs"... I know. Whereas those are 45% homologs only ;-)
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Manu Prestat
wouldn't that be three?
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Adrian Pelin
Haha :facepalm:
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Daniel Standage
I feel like a lot of "stupid mistakes" revolve around betrayed trust and false assumptions
For example:
- Trusting that a downloaded file is actually fully downloaded
- Trusting that an aligner will accept a list of query files instead of just taking the first and ignoring the rest (quiz: which ones am I talking about?)
- Assuming that the quality scores in a FASTQ file are from a great Sanger-encoded run instead of a very poor Illumina-1.3 run
- Assuming chr1 is followed by chr2 not chr10
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Jeremy Leipzig
If you forgive an attempt to be somewhat provocative, my two favorite mistakes are:
Letting academics build software
Academics are in the need to publish papers, and one easy way to do that is to implement an algorithm, demonstrate that it works (more or less), and type it up in a manuscript. BT,DT. But robust and useful software requires a bit more than that, as evidenced by the sad state of affairs in typical bioinformatics software (I think I've managed to crash every de novo assembler I've tried, for instance. Not to mention countless hours spent trying - often in vain - to get software to compile and run). Unfortunately, you don't get a lot of academic credit for improved installation proceedures, testing, software manuals, or especially, debugging of complicated errors. Much better and productive to move on to the next publishable implementation.
Letting academics build infrastructure
Same argument as above, really. Academics are eager to apply to construct research infrastructures, but of course they aren't all that interested in doing old and boring stuff. So although today's needs might be satisfied by a $300 FTP server, they will usually start conjecturing about tomorrow's needs instead, and embark on ambitious, blue sky stuff that might result in papers, but not in actually useful tools. And even if you get a useful database or web application up and running (and published), there is little incentive to update or improve it, and it is usually left to bitrot, while the authors go off in search of the next publication.
Yeah I don't know what why it is so hard for me to remember all the great bioinformatics software that has come from industry, like uhh Eland, or the great standards that have come from industry, like Phred-64 FASTQ.
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Jeremy Leipzig
@Jeremy: I'm not so sure industry is much better, and it's possible that academia is the democracy of development - worst, except for the others. Also, a lot of industry software are add-ons, designed to sell something else. FWIW, Newbler seems to be one of the better assemblers out there, and CLC is at least half-decent as an analysis platform for non-informaticians.
I am fine with point 2, but I have to disagree with 1. Your de novo assembler example is actually not a good one. De novo assembly is very complicated and highly data dependent. I doubt any assemblers work for any data sets, no matter developed by academia or by professional programmers.
What about citations of your paper describing the software? The more people are able to use your software, the more cited it will be. That sounds like an incentive to me, and I try to see it that way when I write code (but I don't publish much code, it's mostly quite ad-hoc stuff).
Ketil repeatedly says in the post that academics don't have incentive to improve their tools, as it's more beneficial to move on to other publications. I say the incentive are citations of your method. Not to mention I regularly see academic software where they care about the things he says academics don't care about. So why would somebody say there are no incentives for improvements, when I can clearly see them and point them out to you?
You do have a point. However, citations are quite rare. One common problem with bioinformatics tools is that people use but seldom cite them properly. Imagine something like bioawk - it would be day to day usage for quite a few people, but it's not seen as something cite-worthy. Good tools have this habit of melding into the background that they don't stand out. Journals are changing this practice now though, with initiatives like STAR methods.
The problem with citing bioawk is that there is no publication to cite. Other tools may not have such problem. But it is true that even I fail to cite some packages I use, usually those that are not required to replicate some results, but are rather just a convenience.
STAR methods looks like a good initiative, too bad I will never send anything to Cell Press, on principle. They care about money above everything else - they are the only publisher that asked me to pay for a COVID-19 paper, at the peak of the pandemic no less.
- off-by-one errors
- regex errors
- parsing a complex alignment/file format incorrectly (e.g. BLAST or GenBank, probably the original rationale for developing BioPerl)
- failing to account for strand
- failing to revcomp sequences
- failing to account for the last element in a file (because of a improper loop condition or no EOL character on last line)
- failing to account for OS dependent line breaks
- using the wrong assembly/annotation/release
- using the wrong genome coordinate system
- using the wrong file (multiple versions, version skew)
- failing to account for nested/intercalated annotation features (e.g. genes)
- assuming all jobs have completed on a cluster
- deleting files
- not randomizing your data properly
- improper use of statistical tests
- not documenting methods fully (to check and correct all of the above)
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Casey Bergman
ouch... brings back bad memories...
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kajendiran56 •
oops.. I did that several times.
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bagdevi.mishra
Using grep to find sequence (or other) IDs without using the -w switch: grep 'seq12' will also find seq121, seq122 and so on.
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Shellfishgene •
IMHO being off by one is the emperor of all bioinformatics mistakes - it rules them all - and probably causes tens of millions of dollars in wasted effort
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Istvan Albert
trying to solve any problem with BioPerl :-)
but the
- '+1' error
- and the
grep > some.fasta
are my favorite mistakes.
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Pierre Lindenbaum
Re-inventing the wheel. So often did I have to debug (or just replace) a bad implementation of a fasta-parser when BioPython/BioPerl have perfect implementations, I don't understand why no-one bothers to use them. 10 minutes in Google can save you 2 days of work and other people a week of work (you save 2 days of programming, they save a week of understanding your program to find the bug)
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Philipp Bayer
I fully agree, re-inventing the wheel is so tempting. We are way too eager to write a few lines of code each time. Plus, because you may have convinced yourself that you can resolve the code in 15 minutes, you don't bother about writing any documentation. In short, there is a very large tendency to re-invent the wheel... many, many times!
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Javier Herrero •
Using other peoples code is all fun and games, until you realise that your package has 106 dependencies, and you only use 1 function from each. Each of those dependencies has its own dependencies, depends on a particular version of gcc (but not the same one as the others), doesn't play nice with some common system used on other peoples systems...
I agree too. Sometimes it's good for practicing purposes to keep on writing simple code, though.
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Manu Prestat
As the nim library docs say, "The great thing about re-inventing the wheel is that you can get a round one."
My main reason for reinventing the wheel is that I want to use much more powerful and general language: Python instead of R. Of course, if the stuff I needed was already in Python/Pandas it would be a different thing entirely.
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Endre Bakken Stovner
Well I have couple:
- Run a batch BLAST job and forgetting to put the
-o something.outoption. Then switching off the monitor and coming the next day to see a bunch of characters in my terminal tar -zxvfwithout checking the tar file before, I have decompressed thousands of files in my current directory assuming they came in their own folder.
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Andres Pinzon •
I gave my Amazon EC2 password to someone in my group who wanted to run something quickly (estimated cost, $2). I received the bill 2 months later: $156. This person forgot to close the instance. This is a 8 months story and I'm still waiting for my reimbursement... Conclusion: don't trust colleagues!
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Manu Prestat
I'll offer this one, which is a bit on the general side: Deletion of data that appear to serve no relevance from the computational side, but which have importance to the biology/biologist. Often, this arises from a lack of clear communication between the two individuals/teams as to what everything means, what it exactly means and why it is relevant to the process being developed.
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Larry_Parnell
Not keeping an adequate notebook.
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Zev.Kronenberg
What is a "notebook"?
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ebrown1955
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marko.petek •
- having manual components to an analysis pipeline (editing data sets running scripts manually)
- Not dealing with error conditions at all. This is one thing that I really noticed when I started with bioinformatics; code that would just merrily continue when it hit incorrect data and output gibberish or fail far away from the bad data. A debugging nightmare.
- Not testing edge and corner cases for input data
- Assuming that your input data is sane; I've run into all sorts of inconsistency issues with public data sets (i.e. protein domains at positions off the end of the protein, etc). Usually fixed promptly if you complain but you've got to find them first.
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Gareth Palidwor
I often encounter problems related to the fact the computer scientists index their arrays starting with 0, while biologists index their sequences starting with 1. Simple concept that drives the noobs mad and even trips up more experienced scientists every once in a while.
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Daniel Standage
Do pathways statistics or gene set enrichment statistics and then represent the list of gene sets as a valuable result, instead using that statistics just as a means to decide which pathways need to be evaluated.
(This is bad for many reasons for instance because the statistical contribution of a key regulatory gene in a pathway is equal to that of 1 out 7 iso-enzymes that catalyze a non-relevant side reaction, and because the significance of a pathway changes when you add a few non-relevant genes, and also because we have many overlapping pathways).
Another typical mistake is to solve problems that nobody has.
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Chris Evelo
these sound like poor judgments (e.g. Clinton-Lewinsky), not stupid mistakes (e.g. dangling chad)
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Jeremy Leipzig
No, I think it is actually wrong to publish a list of pathways without further judgement. I think not doing the judgement is a mistake. But I have to admit that I don't really understand your examples. So maybe my English is not good enough to understand the finesses of the difference between poor judgement and stupid mistakes.
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Chris Evelo
I would define a stupid mistake as falling prey to a trivial but catastrophic pitfall, an error in judgment is more due a fundamental lack of understanding or willful ignorance
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Jeremy Leipzig
In that case you are right, these would be judgement errors.
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Chris Evelo
One mistake: not looking to see that the 0x4 bit in the bitflag column of a SAM (or BAM) file indicates the entry is mapped. RNAME, CIGAR, and POS may be set to something non-null (an actual string!) but these are not meaningful if the 0x4 flag says the read is unmapped.
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Vince Buffalo
I've stepped in that bear trap. Learning to trust the bit flags is an important lesson!
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Zev.Kronenberg
yes the space between * and .fa has bitten me as well. maybe there is an idiot guard against that somewhere?
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Jeremy Leipzig
So this is a (very) late reply, but in case it's still helpful or someone comes across this question like I did, rm -ir will ask before deleting files. Maybe a little annoying to type y a hundred times, but better to do that than lose all your data to a mistyped glob IMHO.
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Duncan Murdock •
From my .bashrc:
alias cp='cp -i'
alias rm='rm -I'
Has saved me quite a bit of headache. The capital I prompts only when you remove more than three files - good when you accidentally type rm some_directory/ * (notice the space)
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Philipp Bayer
Ooh, I never knew about -I, thanks!
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Duncan Murdock •
:) I did the same stupid thing many time!! I lost weeks of works by one click!
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Mchimich •
I was just deleting some unnecessary files from a dir and managed to have a space and an asterisk at the end of the rm command. As soon as I realized what was happening I hit ctrl-c, but important files without backups were already gone. Oh well, it will only take like 2-3 weeks to reproduce them. Also time to edit .bashrc following Philipp's post..
Note that the really stupid mistake here is a bit hidden "important files without backups"
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Chris Evelo
I too have had that moment of dread when I realized I typed rm * /folder versus rm /folder/*! Check out some of the solutions on this forum page, specifically trash-cli. You can set up a trash folder so after deleting files they are not completely gone and can be restored if needed. You would have to manually empty the trash folder or set up a cron job to do so on a regular basis, but this may help circumvent the nightmares listed here!
Masking out sequence in a FASTA file (e.g. s/TAAT/NNNN/ig) where the sequence is formatted, i.e. split onto multiple lines.
This will miss TAAT that is split over the end of one line and the start of the next!
The classic mistake (also mentioned above by Casey) is not being aware the genome assembly effect coordinates.
What kills me the most is the hand editing of data sets.
If you're reading this and do it, please stop -- and start using automated builds -- with clear documentation.
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Blunders •
Having separate files for each sequence.
Of a 454 run.
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Andrewjgrimm •
I wouldn't say it's stupid, but I think a very common mistake is to not correct for batch effects in high-throughput data.
Batch effects can (best-case) hide the real effect that you're looking for, or (worst-case) make it look like your variable of interest is contributing to your findings when it's actually an artifact.
Leek + Irizarry et al. have a sobering review on this here.
Creating a new set of (public) identifiers for your database for entities that already have identifiers in a widely-user public db.
Having unstable identifiers that are publicly available.
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girlwithglasses
Our paper, out this week, is a decent round up of how to avoid identifier-specific issues with your data and that of others. http://dx.doi.org/10.1371/journal.pbio.2001414
tacking on another command line argument without looking through the rest of them
novoalign -a ATCTCGTATGCCGTCTTCTGCTTG -d genome.ndx -F ILMFQ -f query.fq -a -m -l 17 -h 60 -t 65 -o sam -o FullNW
the first adapter argument (-a ATCTCGTATGCCGTCTTCTGCTTG) is negated by the empty second one
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Jeremy Leipzig
Running the bwa/GATK pipeline with a corrupt/incompletely generated bwa index of hg19. Everything still aligned, but one of 2 mates would have its strand set incorrectly. Other than the insert size distribution, everything seemed normal, until the TableRecalibration step downshifted all quality scores significantly and then UnifiedGenotyper called 0 SNPs. 1st time I've seen a problem with step 1 of a pipeline not become obvious until step 5+.
Scripting an hour to do something you could have done in half an hour manually, and then never needing to repeat it again.
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Niek De Klein
but that one is in here already
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Niek De Klein
I've just made one, which cost me a good headache trying to figure out the biology underlying my strange results!
- expecting SAM's
POSfield to be the leftmost position of my mapped read on the '+' strand, and the rightmost position on the '-' strand
Note to self : "Read the manual..."
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Leonor Palmeira
not to mention how much work is to actually get the rightmost coordinate.
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Istvan Albert
Isn't this just POS+length(SEQ)? I'm having doubts now...
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Leonor Palmeira
that only applies if the sequence contains only matches or mismatches, this means edit strings that are composed of a number followed by M (like 76M) . For all other alignments you will need to parse the CIGAR string and build the end coordinate from the start + numbers in the edit string.
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Istvan Albert
Phew... I'm glad I only have matches and mismatches, so I fall in the easy category :-) Thanks a lot for adding this information, this can be a big trap!
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Leonor Palmeira
I have a perl parser that will change the read length bases on the cigar if you ever want / need it.
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Zev.Kronenberg
Thanks a lot! I'll keep that in mind! Or maybe you can share it here as a Tool? or as an answer to this thread : Mapping Reads With Bwa And Bowtie ?
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Leonor Palmeira
Hehe! That's the best idea ever! This thread keeps on giving.
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Istvan Albert
If I understand you correctly, you are saying that this will inflate the number of variants, since many have ambiguous positions? Interesting - do aligners generally guarantee that such ambiguous variants are consistently placed for forward and reverse reads?
I made one a few months ago. I launched a heavy process in a pay-per-use cluster, it was running for one week. I thought, 6 pennies/hr cannot be too much money. I received a bill for $832 usd. I'm not using this cluster again unless I estimate the total cost of the process.
edit: the price is per core
By my count, 6 pennies per hour is $1.44 a day or about $10 a week. How did you get $832?
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Ryan Thompson
maybe its price per CPU and depending upon the size of cluster, BAM!!!
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Sukhi Singh
Possibly: implementing methods that magically generate p-values from non-replicated RNA-seq experiments, possibly as a result to pressure from 'experimentalists'. I really would like to know the history behind their implementation (where they forced by reviewers, or by other groups?). Now we have to explain why those p-values are bogus, and why there are so little significantly differentially expressed genes detected in a non-replicated analysis.
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Michael Dondrup
When using scp, I did this:
scp -r somename@somehost:$home ~/
instead of $home, should use ~/
this created a file named $home in my other account.
used rm $home
and kabum!
should pay attention and look how remove this kind of file before.
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tiago211287
I spent hours to implement R parallel script to fully exploit 64 cores and 250 GB RAM of the server lab. Thus, really proud of myself, I run it on my 4 cores and 8 GB RAM desktop pc. Boom.
I remember once I put a coma in the wrong bracket in some matrix assignment on genotype data and after running the code my laptop froze so hard I had to shut it down by holding the power button. I remember the laptop needed two reboots to get back to normal. After going through the code to see what happened, I realized I assigned a matrix to each cell of itself (or something like that), basically creating an object somewhere around 250 GB in size. My laptop had 8 GB of RAM and about the same of swap (older Ubuntu) and it run out of both within an eye-blink :D
Losing an hour to learn that some files saved on a Mac have a strange 'beginning of file' like character...
Normalize file standards already! x_o
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Eric Normandeau
My common one cat aVeryBigFile.whatever &
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Sukhi Singh
just kill -9 $PID from another session, no?
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Simon Cockell
Good thought but, on a server (I should have told earlier, I commit this on server sessions), your process id's in one login are not known in other login/session.
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Sukhi Singh
I'm pretty sure that ps aux | grep cat from another session will give you the PID of any running cat process on the server.
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Daniel Standage
@brentp, @Daniel cool guys, now this mistake can be rectified :)
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Sukhi Singh
if you don't have other cat job running, you can also type killall cat. Even if you don't see your input, it should work.
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Manu Prestat
I had another good one recently. I was executing an untested bash script for generation of output from two input files on our cluster. I just let it run over night. When I checked in the morning, it had generated about 40 TB worth of output (expectation was about 20 MB). There was a tiny spelling mistake that led to an infinite loop. Oops. I was lucky to check it when I did because there was still a few TB space left so at least other jobs didn't get killed because of it..
I am not joking,
how about forgetting to have a full loaded battery for your wireless keyboard and/or mouse near you, and the current one inside is running out of power?
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Antonio R. Franco
I have spent hours, in repeated occasions, looking for a mysterious error in a perl script that at the end was simply a = instead of a == within an IF statement.
Another recurrent mistake: not documenting what I did and what those scripts do in the belief that everything is so intuitive, organised, simple and natural that it won't be necessary. Then, sometime after, I have to spend hours trying to guess what all that mess was.
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abascalfederico
I'm sure someone has mentioned this, but running something like:
bcftools view -S something.txt in.bcf > in.bcf
Goodbye in.bcf, I hardly knew ye.
Also memory management for Java programs on an HPC (beagle I'm looking at you). I love spending hours trying to guess exactly how much memory the JVM is going to use and toggling -Xmx/-Xms flags.
I feel your pain. A handy way to avoid this is to set -o nocolobber, which prevents you from redirecting into existing files. See: https://mywiki.wooledge.org/NoClobber
What about building an interface not aimed at a community of (fellow) Biologists?
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Andra Waagmeester
that might be stupid and it might be a mistake but it isn't a "stupid mistake". see comments under Chris Evelo's post.
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Jeremy Leipzig
Then I will conclude with the same comment as Chris.
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Andra Waagmeester
I have an opposite mistake. I accidentally replace a string in the whole document and something I didn't want to replace gets replaced. Now I visually select the area where I want to replace...
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Sequencegeek •
Just read this article: "How Not To Be A Bioinformatician" Thought it would be interesting to post here....
Then this might fit as well: "How to be a bioinformatician"
Some really great comments here, nice to know that such things happen to all genii ;). I have to say my most painful moments relate to my assumption that data obtained elsewhere is correct in every way. I also remember early in my career, using PDB files and realising that sometimes, chains are represented more than once, thus when manually checking calculations involving atomic coordinates, being utterly perplexed and wanting to break my computer. Oh the joys of Bioinformatics.
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kajendiran56 •
Using a statistical test on data that does not satisfy the assumptions of that test.
For example, finding differentially-expressed genes by doing ANOVA on log2(FPKM).
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Ryan Thompson
Assuming that the gene IDs in "knownGenes.gtf" from UCSC are actually gene IDs. Instead they just put the transcript ID as the gene ID.
This just caused me a bit of pain when doing read counting at the gene level. Basically, any constitutive exon in a gene with multiple splice forms was ignored because all the reads in that exon were treated as ambiguous.
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Ryan Thompson
Using the same output (> oh.shit) for multiple commands.
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axelwilhelm
These are just a few, but thought worth sharing:
- Not having a copy of VERY IMPORTANT file as backup.
- Forgetting to save parameters used, while running a tool and again start hunting them after few days.
- Irrelevant folder/file names, especially not having extensions like fasta or fastq at the end of file.
- Not having a consolidated folder/place, where all scripts and programs lie.
- Upgrading OS without IT support or prior knowledge, and completely losing the GUI, which needs reinstall of OS again.
- using UNIQ command in linux, without SORTING the data.
- Not removing trailing and leading space of variable, before matching it.
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Prakki Rama
How about writing a tool and being convinced it works perfectly, so you start testing it on a complete dataset instead of testing it first on a subset and finding out after it ran for an hour or so that you made a tiny mistake somewhere. Sooo much time wasted that I'll never get back :P
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Lesley Sitter
Spending a few months to find an interesting correlation in data and then presenting to the lab that sequenced to find out they changed coverage on the last few samples!
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elia.brodsky
Since no one mentioned.
The uppercase/lowercase error.
Sometimes, you need to distinguish between "atgc" and "ATGC". But in most cases, they mean the same thing. So always convert any string you met to uppercase if you do not need to distinguish.
I feel spending my whole Ph.D. debugging this. Hope it helps for others.
Running statistical analyses with no understanding of the tests your using, why you're using them, when it's appropriate to use them, how your data needs to be formated, normalize, or scaled to use them... but hey, you made a volcano plot... so it must be publication quality. right? read the damn paper...
A double mistake combo, 1 - use tar to compress a single file and, 2 - inverting the command arguments
tar cvfz file file.tgz
instead of
tar cvfz file.tgz file
Bye bye file!
It happened to me so many times, that I was considering doing an imagery brain check up.
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Manu Prestat
- Forgetting that human chromosomes are named differently by UCSC and Ensembl (UCSC names have the 'chr' prefix)
- Assuming the alphabetical order of human chromosome names is "chr1", "chr2", "chr3", ... when in fact it is "chr1", "chr10", "chr11", ...
- Forgetting that there is a fifth possible character in a DNA sequence: N (for unknown)
You also occasionally see IUPAC codes pop up in fasta sequences.
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Chris Miller
- Forgot to use
-nin numerical sorting of positions in a bed file. - Not using
-kflag in sort for a specific column, instead sorting all possible stuff in it.
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Bioinformatics_NewComer
Mixing between hg18, hg19 and yes new one GrCh 38 too !! :)
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always_learning
A very general one:
Using packages without trying to understand what they actually do.
A more specific one:
Assume that the human mitochondrial reference sequence is the ancestral sequence.
Opening a .clc file in terminal only to find out it was a binary! #facepalm
I have a bit of a different take:
The most pervasive and damaging problem afflicting bioinformatics studies is the failure to curate covariate information, resulting in problems of separation and/or complete separation.
This problem is particularly sinister because this frequently occurs long before the bioinformatician is consulted on the project, meaning the project already has unnecessary limitations before the data scientist/statistician/what-have-you receives the data.
At minimum, this will limit statistical power, in certain cases, it means there is a confound that can't be mitigated without meta-analytics or extreme ends. In my experience this affects, oh I don't know, >70% of labs, including world-class, well-known labs, who don't retain a statistician.
- Creating new result and forget to remove past one for example : result1, result2 , result 30May, result20june, result_final, result_final_final !!!
- Holding the zip version after unzipping the files
- Holding sam format files after converting to bam format
- Creating multiple bam in GATK and forgetting to remove them
- Changing the linux configuration core during installing the softwares !!! crashing the linux and install new linux !!
- Forgetting to save the pipelines used in Bash
- Forget to put dev.off() in R code
- Using rm * without careful watching the file list
Points 1 and 2 are not really mistakes, I never delete older versions. Instead, I create files with timestamps. Unless you know you'll never need the older version (and still have code/documentation to create the older version if necessary), deleting it is not a smart thing to do. I'd rather delete unzipped files after using them than delete the zip archive.
Points 1-4 are all about space saving. Of these, only #3 is problematic in all scenarios as no information is lost. #4 is probably specific to your way of using GATK.
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thanks for censoring my answer!
meta: should this Q be community-wiki?
good way to boost reputation.
what's the mean by said generate random genomic sites without avoiding masked (NNN) gaps? more detailed? do not understand.
see this?
http://genome.ucsc.edu/cgi-bin/das/hg19/dna?segment=chr1:1,10000
you wouldn't want to sample from it
Gotten it. Thank you.
Staying in the office all day
grep XX A.fas>A.fas This comand result in the empty A.fas
This is literally the second answer: What Are The Most Common Stupid Mistakes In Bioinformatics?
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