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I have a gtex variant file- the head of which looks as follows:

phenotype_id                                    variant_id     
chr1:15947:16607:clu_36198:ENSG00000227232.5    chr1_13550_G_A_b38  ...
chr1:15947:16607:clu_36198:ENSG00000227232.5    chr1_14671_G_C_b38  ...
chr1:15947:16607:clu_36198:ENSG00000227232.5    chr1_14677_G_A_b38  ...
chr1:15947:16607:clu_36198:ENSG00000227232.5    chr1_16841_G_T_b38  ...

Effectively I would like to be able to lookup the variants inside a particular gene (the file is sorted) and put them in a temporary file: E.g. If the variants in gene "ENSG00000148481- MINDY3" are on line number 87528225 to 87536766- effectively what I would like is the equivalent to zcat file.gz | sed -n '87528225,87536766p' > MINDY3.txt. However zgrep ENSG00000148481 file.gz is just as fast as the above...

Hence I thought tabix would be the right tool for this-

I would like to tabix index it to make lookups faster. It is gzip compressed and I will firstly have to do:

zcat gtex.txt.gz | bgzip > gtex.txt.bgz

However I am not quite sure how to proceed from there given that the data is not tab-delimited.

As a trial I tried the first 1000 lines:

zcat gtex.txt.gz | head -n 1000 | bgzip > gtex_1000.txt.bgz

./tabix -p bed gtex_1000.gz #index as a bed file
[get_intv] the following line cannot be parsed and skipped: chr1:15947:16607:clu_36198:ENSG00000227232.5        chr1_13550_G_A_b38     ......

./tabix -p vcf gtex_1000.gz #index as a vcf file
Indexing as a bed file results in a warning while indexing as a vcf gives no warning yet either way when I try to retrieve a sequence:

./tabix test.gz chr1:15000:17000

It returns nothing.

I am starting to think that I will just have to write a script that splits on the ':' and writes the data to a new file.... and then index that file- which will take a huge amount of time ... Does anyone know of a trick to index the files with unconventional delimiting?

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  • $\begingroup$ Suppose that you could successfully creat an index file for your txt file, which program would be used to read it? $\endgroup$
    – Phoenix Mu
    Aug 29 '20 at 2:21
  • $\begingroup$ @PhoenixMu see the way that I have used sed in the updated question... this was my plan... although this was the same speed as grep $\endgroup$ Aug 31 '20 at 16:25
  • $\begingroup$ I think tabix only works for bed and vcf format. Your file is not in bed format? $\endgroup$
    – Phoenix Mu
    Sep 1 '20 at 17:13
  • $\begingroup$ Yes it's not in bed format as the coordinate columns are : delimited and the file is too big to justify producing a copy with properly delimited columns- I am in the process of making an index file myself and will post an answer if it works $\endgroup$ Sep 2 '20 at 9:06
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Tabix files need a name and a genomic coordinate at least. Tabix can be (ab)used by creating a fake genomic coordinate and then it just indexes names but not sure I would recommend this usage. What is your actual expected application of this?

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  • $\begingroup$ Hi @Colin thanks for getting to me- I just want to be able to take out all variants inside a particular gene- for example if the variants in gene "ENSG00000148481- MINDY3" are on line number 87528225 to 87536766- effectively what I would like is the equivalent to zcat file.gz | sed -n '87528225,87536766p' > MINDY3.txt Hence I thought tabix would be the right one for this $\endgroup$ Aug 31 '20 at 8:12
  • $\begingroup$ Here is an example of a tabix file that has been hacked up to allow "free text query". target.wustl.edu/ENCFF000ARO_ALL.iteres.loci.gz So they can query tabix file.txt "A(n)" and because there are many lines starting with A(n) it will return all of them $\endgroup$
    – Colin D
    Aug 31 '20 at 15:48
  • $\begingroup$ Can also check out other options for text indexing unix.stackexchange.com/questions/3086/… $\endgroup$
    – Colin D
    Aug 31 '20 at 16:08
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I proceeded as follows:

import gzip
import sys

qtls=['sqtls','eqtls']
tissues=['Adipose_Subcutaneous', 'Adipose_Visceral_Omentum', 'Adrenal_Gland', 'Artery_Aorta', 'Artery_Coronary', 'Artery_Tibial', 'Brain_Amygdala', 'Brain_Anterior_cingulate_cortex_BA24', 'Brain_Caudate_basal_ganglia', 'Brain_Cerebellar_Hemisphere', 'Brain_Cerebellum', 'Brain_Cortex', 'Brain_Frontal_Cortex_BA9', 'Brain_Hippocampus', 'Brain_Hypothalamus', 'Brain_Nucleus_accumbens_basal_ganglia', 'Brain_Putamen_basal_ganglia', 'Brain_Spinal_cord_cervical_c-1', 'Brain_Substantia_nigra', 'Breast_Mammary_Tissue', 'Cells_Cultured_fibroblasts', 'Cells_EBV-transformed_lymphocytes', 'Colon_Sigmoid', 'Colon_Transverse', 'Esophagus_Gastroesophageal_Junction', 'Esophagus_Mucosa', 'Esophagus_Muscularis', 'Heart_Atrial_Appendage', 'Heart_Left_Ventricle', 'Kidney_Cortex', 'Liver', 'Lung', 'Minor_Salivary_Gland', 'Muscle_Skeletal', 'Nerve_Tibial', 'Ovary', 'Pancreas', 'Pituitary', 'Prostate', 'Skin_Not_Sun_Exposed_Suprapubic', 'Skin_Sun_Exposed_Lower_leg', 'Small_Intestine_Terminal_Ileum', 'Spleen', 'Stomach', 'Testis', 'Thyroid', 'Uterus', 'Vagina', 'Whole_Blood']

gene_old=''


def index(tissue,qtl,gene_old):
        counter_old,counter=1,1
        if qtl=='sqtls':
                path='/path/to/file/'+tissue+'.v8.sqtl_allpairs.txt.gz'
        else:
                path='/path/to/file/'+tissue+'.allpairs.txt.gz'
        f = gzip.open(path, 'r')
        next(f)
        for line in f:
                try:
                        line=line.decode()
                        line=line[:line.find('\t')]
                        gene=line[line.rfind('ENS'):].split('.')[0]
                        #print(gene,gene_old,counter_old,counter)
                        with open(qtl+'_'+tissue+'.idx','a') as indexed:          
                                 indexed.write(str(gene_old)+'\t'+str(counter_old)+'\t'+str(counter)+'\n')
                        gene_old=gene
                        counter +=1
                        counter_old=counter
                except IndexError:
                        print('tissue,qtl,gene_old,counter')
                        counter+=1
        f.close()


for qtl in qtls:
        for tissue in tissues:
               qtl=row.qtls
               tissue=row.tissues
               print(qtl, tissue)
               index(tissue,qtl,gene_old)

The above script writes an index for each gene which should look as follows (took 2 days to finish all files):

ensid    row_start    row_end
......
ENSG00000230337     1526391 1534329
ENSG00000171819 1534330 1542321
ENSG00000198793    1542322 1550178
ENSG00000120942  1550179 1558010
.....

And to get a gene of interest you will have to look up the coordinates for an ensemblid/gene and for example:

zcat Brain_Nucleus_accumbens_basal_ganglia.v8.sqtl_allpairs.txt.gz | sed -n '1550179,1558010p;1558011q' > ENSG00000120942.txt
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