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Category: Bioinformatics

Couldn’t delete a failed R package installation

Couldn’t delete a failed R package installation

Today I faced a strange thing, while I tried to install an update to one of my R-packages. As usually, I installed the latest version from it like this


But the installation failed, and when I tried to reinstall it, I got this error message:

Installing package into ‘/homeappl/home/<user>/R/x86_64-redhat-linux-gnu-library/4.1’
(as ‘lib’ is unspecified)
ERROR: failed to lock directory ‘/homeappl/home/<user>/R/x86_64-redhat-linux-gnu-library/4.1’ for modifying
Try removing ‘/homeappl/home/<user>/R/x86_64-redhat-linux-gnu-library/4.1/00LOCK-GenomicTools’
Warning message:
In i.p(...) :
  installation of package ‘/tmp/Rtmp<...>Lv/file3c36<...>34/GenomicTools_0.2.11.tar.gz’ had non-zero exit status

So, I tried to go in said directory and delete the folder manually and there I received another error:

rm: cannot remove '00LOCK-GenomicTools/GenomicTools/libs/.nfs00000001002e2<...>d': Device or resource busy

I tried this and this, but nothing helped to delete that folder, it kept mocking my that the device is busy. Eventually, it helped just to rename the folder list this

mv 00LOCK-GenomicTools/ 00LOCK-GenomicTools-deleteThis/

It is now still hanging there in the folder, but I was able to reinstall the R-package and now I need to revisit the folder in a few days and check, if the device is still busy or if I can delete it then…

Take a random sample of size k from paired-end FASTQ

Take a random sample of size k from paired-end FASTQ

Today I wrote a bash script that creates a random subset of a paired-end FASTQ file pair. It requires the names of the two FASTQ-files as input and also the amount of reads that the sample should have.

The script is mainly based on this Blog post. This is a rather rough code and it could be more user-friendly and allow for more options, but in its current form, it does what I need it to do.


round() {
    printf "%.2f" "$1"

# Input test
 if ! [[ $sample =~ ^-?[0-9]+([.][0-9]+)?$ ]]; then 
>&2 echo "$sample is not a number"; exit 1; 


if [ $extension1 == "gz" ]; then
  gunzip $file1;
if [ $extension2 == "gz" ]; then
  gunzip $file2;

lines=$(wc -l < $file1)
echo $lines
echo $sample

if (( $(awk 'BEGIN {print ("'$sample'" <= 1)}') )); then
  sample=$(awk 'BEGIN {printf("%.0f", "'$sample'" * "'$lines'")}')

echo $sample

paste $file1 $file1 | \
awk '{ printf("%s",$0); n++; if(n%4==0) { printf("\n");} else { printf("\t");} }' | \
awk -v k=$sample 'BEGIN{srand(systime() + PROCINFO["pid"]); }{ s=x++<k?x- 1:int(rand()*x);
                  if(s<k)R[s]=$0}END{for(i in R)print R[i]}' | \
awk -F"\t" -v file1=$fn1 -v file2=$fn2 '{print $1"\n"$3"\n"$5"\n"$7 > file1;\
                                         print $2"\n"$4"\n"$6"\n"$8 > file2}'
if [ $extension1 == "gz" ]; then
  gzip $fn1;
  gzip $file1;
if [ $extension2 == "gz" ]; then
  gzip $fn2;
  gzip $file2;
New Bovine Genome Comparison

New Bovine Genome Comparison

Since 2014 the standard for genome studies in bovine was the UMD 3.1 genome, e.g. for download here:


However, a few days ago a new assembly was release, called ARS_UCD1.2.This assembly can be downloaded here:

Just to get a quick impression, I compared both assemblies and checked for their similarities using LAST .

First, I created a LAST database like this

lastdb -P0 -uNEAR -R01 $FOLDER/UMD31/UMD31-NEAR $FOLDER/UMD31/UMD3.1_chromosomes.fa

Then, I determined the substitution and gap frequencies

last-train -P0 --revsym --matsym --gapsym -E0.05 -C2 $FOLDER/UMD31/UMD31-NEAR $FOLDER/ARS/ARS_UCD12.fna > $FOLDER/UMD-ARS.mat

After the training, the blasting was performed (here is the parallel part of the slurm script)

chr=($(ls $FOLDER/ARS/chr*));

lastal -m50 -E0.05 -C2 -p $FOLDER/UMD-ARS.mat $FOLDER/UMD31/UMD31-NEAR ${chr[$SLURM_ARRAY_TASK_ID]} | last-split -m1 > UMD-ARS-$SLURM_ARRAY_TASK_ID.maf

As I ran the blasting parallel for each chromosome, the header of the files needed to be removed

cat *.maf > all.maf
sed '/^#/ d' < all.maf > temp.maf
head -n 22 all.maf > headerLines
cat headerLines temp.maf > alignments.maf

Finally, the merged simple-sequence alignments were discarded, the alignments were converted to tabular format, and alignments with error probability > 10^-5 were discarded:

last-postmask alignments.maf |
maf-convert -n tab |
awk -F'=' '$2 <= 1e-5' >

And for that tab file was then the dotplot created

last-dotplot -x 4000 -y 4000 alignment.png

This is how the dotplot looks like, it seems pretty much the same genome, but has in some areas clearly changed it! (Open it and zoom to the diagonal to see the differences)


For the steps, I followed the tutorial here: