Bioinformatics Scientist Interview questions in Singapore

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Bioinformatics Scientist interview questions shared by candidates

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Marshfield Clinic
Bioinformatics Scientist was asked...5 June 2018

Can you manipulate bclfastq files?

2 Answers

I described the pipeline I constructed.

lots of script can do bclfastq, why ask this question?

Personal Genome Diagnostics

Do you feel you would fit in a culture of rapid-change?

2 Answers

I hedged my bets. I said that I was fine with rapid-change as long as the goals were clearly defined each time they changed. Less

Yes I do no I will be a good person for the position cause I'm a team player and I like meet different people Less

Veracyte

Have you ever encountered batch effect or any technical effect. What was the impact on your data and how do you control for these unwanted variables.

1 Answers

Use the ComBat function from the SVA Bioconductor package to combat batch effect

Pacific Biosciences

Asking me about NGS experience, general and w/ PacBio.

1 Answers

Described NGS functions in previous jobs.

Natera

how to convert SAM to BAM files?

1 Answers

samtools view -Sb >

Intermountain Health

how do you handle conflict

1 Answers

I usually take a time out to calm down, review priorities and what actually need to be communicated and then follow up with employee. Less

Twist Bioscience

Some coding and statistics questions, some questions about NGS pipelines.

1 Answers

Did you have to do a drug test?

What distribution is single-cell RNA-seq data? Why is it that distribution? How do you deal with integrating multiple data sets with different distribution.

1 Answers

Negative binomial distribution

Seven Bridges

Process of obtaining raw genetic data up until the point of bioinformatic processing?

1 Answers

I talked about the entire process, from biochemical analysis of sequencing up until different segments of bioinformatic processing of raw data. Less

BenevolentAI

NGS data analysis workflow/pipeline and tools

1 Answers

The current "best" tools for differential expression analysis, e.g. DESeq2 and EdgeR, incorporate normalization factors accounting for library size and composition. Pointedly, these tools do not "just" normalize prior to analysis, they include the normalization factors as features within the model. If you are looking to utilize a neural network, hierarchical bayesian, or other type of machine learning approach to differential expression, determining the appropriate method of normalization will be a make or break point. Less

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