The E-value provides information about the likelihood that a given sequence match is purely by chance. The lower the E-value, the less likely the database match is a result of random chance and therefore the more significant the match is. Empirical interpretation of the E-value is as follows. If E < 1e - 50 (or 1 × 10-50), there should be an extremely high confidence that the database match is a result of homologous relationships. If E is between 0.01 and 1e - 50, the match can be considered a result of homology. If E is between 0.01 and 10, the match is considered not significant, but may hint at a tentative remote homology relationship. Additional evidence is needed to confirm the tentative relationship. If E > 10, the sequences under consideration are either unrelated or related by extremely distant relationships that fall below the limit of detection with the current method. Because the E-value is proportionally affected by the database size, an obvious problem is that as the database grows, the E-value for a given sequence match also increases. Because the genuine evolutionary relationship between the two sequences remains constant, the decrease in credibility of the sequence match as the database grows means that one may “lose” previously detected homologs as the database enlarges. Thus, an alternative to E-value calculations is needed

A bit score is another prominent statistical indicator used in addition to the Evalue in a BLAST output. The bit score measures sequence similarity independent of query sequence length and database size and is normalized based on the rawpairwise alignment score. The bit score (S) is determined by the following formula:

S = (λ × S − lnK)/ ln2

where λ is the Gumble distribution constant, S is the raw alignment score, and K is a constant associated with the scoring matrix used. Clearly, the bit score (S) is linearly related to the rawalignment score (S). Thus, the higher the bit score, the more highly significant the match is. The bit score provides a constant statistical indicator for searching different databases of different sizes or for searching the same database at different times as the database enlarges.

Cited by Manoj Kumar Gupta .

https://www.researchgate.net/post/Identity_score_or_e-value-whats_the_better_measure_for_species_identification_in_BLAST

The pic attached is not a blast result. The result will be the one you get in next step. You could easily identify the best blast hit. Rule of thumb, top blast hit is the best candidate.

Dont know what sequencing you did, i guess it wont be able to give you 100% strain level hit, still you can try.

@Abhijeet Singh, I know how to do BLAST. I think you did not noticed all the attached images.my question was pertaining to some uncultured bacterial strains. i got my answer though. Thanks for your attention :)

Here is a paper in which DGGE analysis is done on the rhizosphere soil of the plant cultivated for different span of time for the assessment of fungal and bacterial diversity. Have a look at this publication, It could be useful for you.

Article Assessment of the Diversity of Pseudomonas spp. and Fusarium...

Thanks Muhammad umar khan