Updated actions

.github/workflows/filterBAM_ci.yml

@@ -11,8 +11,8 @@ jobs:
       - uses: actions/checkout@v2
       - uses: conda-incubator/setup-miniconda@v2
         with:
-          python-version: 3.9
-          mamba-version: "*"
+          python-version: "3.9"
+          solver: "libmamba"
           channels: conda-forge,bioconda,defaults
           channel-priority: true
           environment-file: environment.yml

README.md

@@ -241,7 +241,7 @@ filterBAM filter --bam c55d4e2df1.reassigned.bam --bam-filtered c55d4e2df1.dedup
 
 **--min-read-ani**: Minimum average read ANI that a reference has
 
-**--sort-by-name**: Sort filtered BAM file by read name so it can be used in [metaDMG](https://metadmg-dev.github.io/metaDMG-core/)
+**--sort-by-name**: Sort filtered BAM file by read name so it can be used in [metaDMG](https://github.com/metaDMG-dev/metaDMG-cpp)
 
 **--sort-memory**: Memory used for each thread when sorting the filtered BAM file
 
@@ -349,7 +349,7 @@ $$g^*(r_i) = \arg\max_{j} P(r_i|g_j)$$
 
 ### Applications and recommendations
 
-One of the main applications of **bam-filter** is to reliably identify which potential organisms are present in a metagenomic ancient sample, and get relatively accurate taxonomic abundances, even when they are present in very low abundances. The resulting BAM file then can be used as input for [metaDMG](https://metadmg-dev.github.io/metaDMG-core/). We rely on several measures to discriminate between noise and a potential signal, analyzing the mapping results at two different levels:
+One of the main applications of **bam-filter** is to reliably identify which potential organisms are present in a metagenomic ancient sample, and get relatively accurate taxonomic abundances, even when they are present in very low abundances. The resulting BAM file then can be used as input for [metaDMG](https://github.com/metaDMG-dev/metaDMG-cpp). We rely on several measures to discriminate between noise and a potential signal, analyzing the mapping results at two different levels:
 
 - Is the observed breadth aligned with the expected one?
 - Are the reads spread evenly across the reference or they are clumped in a few regions?