There was a reddit post about installing Arch on NTFS3 partition. Since Windows and Linux doesn't have directories with same names under the /(C:\), I thought it's possible, and turned out it was actually possible.
If you are not familiar to Linux, for example you've searched on Google "how to dualboot Linux and Windos" or brbrbr... you mustn't try this. This is not practical.
| diff --git a/src/core/lib/gpr/log_linux.cc b/src/core/lib/gpr/log_linux.cc | |
| index 561276f0c2..1af0935e1f 100644 | |
| --- a/src/core/lib/gpr/log_linux.cc | |
| +++ b/src/core/lib/gpr/log_linux.cc | |
| @@ -40,7 +40,7 @@ | |
| #include <time.h> | |
| #include <unistd.h> | |
| -static long gettid(void) { return syscall(__NR_gettid); } | |
| +static long sys_gettid(void) { return syscall(__NR_sys_gettid); } |
| (defun new-copyright () | |
| "Generate new copyright string." | |
| (format-time-string "Copyright %Y Michael M. Hoffman <michael.hoffman@utoronto.ca>")) | |
| (define-auto-insert 'python-mode | |
| `( | |
| "Description: " | |
| "#!/usr/bin/env python3.6" \n | |
| "\"\"\"" (setq basename (buffer-file-basename)) ": " str \n | |
| "\"\"\"" \n \n |
this document looks at the depth at a particular position in a BAM file a user sent me, at position 14712.
I discuss in the comments what settings might be related to the coverage differents
The major variables between tools and the scores they report for coverage are related to the filters that are by default applied. Tools that report a lower score generally include duplicate and qc vendor fail filters by default. In this test at a particular position, these tools reported 74 reads.
Scores that are higher have no filters applied. In this test at a particular position, these tools reported 423.
| #!/usr/bin/env python | |
| import re | |
| import gzip | |
| import argparse | |
| from collections import defaultdict | |
| class Alignment: | |
| def __init__(self, in_r_start, in_r_end, in_q_start, in_q_end, in_cigar, in_strand, in_num_matches, in_aln_len, in_num_mismatches): |
GFF is a common format for storing genetic feature annotations. In the case of gene annotations, subsets of elements are split over multiple lines, as things like exons and CDS features will have gaps based on the full genome sequence. Therefore, while it is easy to extract exon and CDS lines, it can be difficult to associate them together based on a parent (e.g., transcript) ID and perform downstream operations. Even extracting the full CDS sequence using a GFF file can be tricky for this reason, even though it seems trivial.
Here we'll overcome this difficulty using the gffread tool. Installation is pretty easy and is documented in the GitHub README. gffread has a lot of options, but here we'll just document one that extracts the spliced CDS for each GFF transcript (-x option). Note that you can do the same thing for exons (-w option) and can also produce the protein sequence (-y option).
Let's extra
OrthoMCL is the leading piece of software for inferring orthologs across several organisms. In this tutorial I will provide detailed instructions for running a set of protein annotations through OrthoMCL.
OrthoMCL, and it's dependencies, must be installed. Detailed information on this tool and its installation can be found here. I actually used a slightly modified version of OrthoMCL that was made available by the author of the orthomcl-pipeline (see below). There isn't much details on the ways this is different from the existing OrthoMCL, but this is available here.orthmcl-pipeline must also be installed, as this is how we will automate the OrthoMCL process. Detailed information on this tool and its installation can be found [here](https
Please see the most up-to-date version of this protocol on my blog at https://darencard.net/blog/.
When annotating genomes it is often desireable to know the overall structure of genes, including information like exon and intron lengths among other metrics. Here is a program genestats that will calculate such measures for a user.
#!/usr/bin/env bash
usage()
Please see the most up-to-date version of this protocol on my blog at https://darencard.net/blog/.
MAKER is a great tool for annotating a reference genome using empirical and ab initio gene predictions. GMOD, the umbrella organization that includes MAKER, has some nice tutorials online for running MAKER. However, these were quite simplified examples and it took a bit of effort to wrap my head completely around everything. Here I will describe a de novo genome annotation for Boa constrictor in detail, so that there is a record and that it is easy to use this as a guide to annotate any genome.