Bioinformatician's Pocket Reference !!

It is amusing how brain of bioinformaticians work! Learning a new programming language for days feels so much of fun that making 5 minute discussion with neighbours (unless under special circumstances!) in our own mother-tongue. Today every bioinformatician keeps more than few languages and core IT toolkits on their plate. It has become mandatory to be able to mould different code snippets to build our own custom workflows, and thus keeping syntax at our fingertips has become essential.

Although Google is best way to get syntax problem solved, it is not a bad idea to keep reference sheets is our smartphones or stick out some printed sheets on the back of your door, in the old fashion way!!



    1) Apache

    2) Awk/Gwak

    3) C

    4) C++

    5) Debian

    6) Git

    7) HTML

    8) Java

    9) Mathematica

    10) Matlab

    11) MySQL

    12) Perl

    13) PHP

    14) Python

    15) Screen

    16) Ubuntu

    17) UNIX

    18) Vim

These are handpicked reference sheets and you may encounter various other versions of these over Internet. If you find any version of reference sheet which is worth sharing, feel free to paste the link below.

At the end, I sincerely acknowledge the authors who put their efforts in designing these informative reference sheets and made it available for us.

Gene Ontology (GO) Enrichment Analysis in Novel Transcriptomes using BiNGO!!

A greater hurdle while dealing with differentially expressed transcripts in novel organisms is the Gene Ontology (GO) enrichment analysis and their visual interpretation.

To date there are several open-source applications available to extract GO terms corresponding to protein/nucleotide sequences (A detailed list can be accessed here, However, the best I have experienced for the De novo transcripts is InterProScan), and to perform enrichment analysis (A detailed list is here). Most of these enrichment tools work like a charm for model organisms, but only handful of them support the incorporation of custom annotations. One such tool is BiNGO (Biological Networks Gene Ontology tool), an open-source Java plug-in of Cytoscape. BiNGO can be used either on a list of genes, or interactively on subgraphs of biological networks visualized in Cytoscape. BiNGO maps the predominant functional themes of the tested gene set on the GO hierarchy.

In order to use BiNGO for novel organisms, one need to provide a custom annotation file (CAF). In principle, CAF contains the gene/transcript and GO relationship, with one relationship per line, eg.

XLOC_000001=0005515
XLOC_000001=0008270
XLOC_000001=0016491
XLOC_000002=0055114
XLOC_000003=0016491
.
.
XLOC_999999=9999999


The left value is the transcript name and right value is the GO category (without the prefix, 'GO:') obtained using InterProScan or synonymous tool.

The first line of GAF should always be:

(species=Custom_species)(type=Biological Process)(curator=GO)

You can choose to change species name from "Custom_species" to something else. Once the building of GAF (GAF.txt) is complete for all the annotated transcripts. It can be used in place of "Select organism/annotation" by choosing "Custom" option. (As shown in the figure below)

 

Additionally, one can also choose to switch to a newer ontology (obo) file downloaded from geneontology.org download page. After providing gene list of interest and choosing the appropriate options, hit the "Start BiNGO" button to start the analysis.


Cytoscape together with BiNGO offers several downstream network grooming options, which you may find useful. For more on this, visit BiNGO and Cytoscape user guides. Hope this helps in your endeavor.